Loading...

Table of Content

    , Volume Issue
      
    null
    2014, 21(2):  168. 
    Asbtract ( )  
    References | Related Articles | Metrics

    null

    null
    2014, 21(2):  172. 
    Asbtract ( )  
    References | Related Articles | Metrics

    null

    null
    2014, 21(2):  178. 
    Asbtract ( )  
    References | Related Articles | Metrics

    null

    null
    2014, 21(2):  182. 
    Asbtract ( )  
    References | Related Articles | Metrics

    null

    A Survey of Diagnosis Methods for Wind Power System
    SHEN Yan -xia，LI Fan
    2013, 20(5):  789-799. 
    Asbtract ( )  
    Related Articles | Metrics

    Abstract: Wind power systems are often installed where is remote，inaccessible or the climate is not suitable for human to stay for long
    time． So the traditional scheduled maintenance and breakdown maintenance can not meet the demands． It is very essential to ensure re-
    liable and stable operation，and to reduce the cost of maintenance，condition monitoring and fault diagnosis of wind power system． The
    existing fault diagnosis methods for the main failure components of wind power system，including gear boxes，generator，power electronic
    devices，blade and so on，were introduced and classified． This work will provide an effective reference to the improvemet of the reliability of wind power system，reduction of cost and promoting the engineering process．

    Automatic Control System of Flotation Processes
    LI Hai-bo，CHAI Tian-you，YUE Heng
    2013, 20(5):  796-799. 
    Asbtract ( )  
    Related Articles | Metrics

    According to the conditions of the low level of automation and low labour productivity，an automatic control system for flotation
    process was designed and developed innovatively based on the ControlLogix series software and hardware platform of Ｒockwell Company．
    The structure and function of the control system are introduced carefully． The control strategies of the pulp level，the air flowrate
    and the flotation reagent feeding are described in detail． The control software and human － machine interface are designed and developed．
    The actual industrial application results show that the control system operates steadily，safely and reliably，the worker labor intensities
    are decreased obviously，and the work condition is improved，the competitiveness of the enterprise is enhanced．

    Decentralized Control for Interconnected Systems with Arbitrary Topology and Communication Failure
    YU Miao，LU Chao
    2013, 20(5):  800-804. 
    Asbtract ( )  
    Related Articles | Metrics

    A analysis method of the problems of interconnected systems and the decentralized controller design method are presented in
    this paper． That the topology of the interconnection is arbitrary and the exchanged information between subsystems is lost cause the unreliable
    link． Firstly，the stochastic variable responsible for the situation of the lossy communication is regarded as a source of model uncertainty，
    and the system is modeled in linear fractional transformation． Then the robust control theory is employed for system analysis，
    and the largest probability of communication failure，which is tolerated by the interconnected systems keeping mean square stable，can
    be obtained． Decentralized state feedback controllers are designed to ensure that the whole systems are mean square stable for a given
    communication failure rate，based on the technique of linear matrix inequalities． Finally，an illustrative example of power network
    which is a part of China southern power grid is presented finally to show the effectiveness of the proposed model and method． Simulation
    results demonstrate that when the communication faults occur between the power components in the China southern power grid，using the
    method described in this paper can make the network well designed and wide-area controlled and the local power network mean square
    stable．

    Parameter Identification Method of 6-axis Industrial Robot
    CAI Jin-da，ZHANG Jian-hao，QIN Xu-xiang
    2013, 20(5):  805-808. 
    Asbtract ( )  
    Related Articles | Metrics

    he position and pose accuracy of the robot end depends on the geometrical parameters accuracy of each joint． An easy and practical method of parameter identification method is put forward to improve the pose accuracy． Using the robot kinematics equation depending on D-H algorithm，the relationship between the end and each joint is obtained． This particular method as well as the corresponding experiment is designed to solve the problems in the identification process，the actual geometric structure parameters are obtained according to the accurate measurement by laser tracker． The experimental results verify the effectiveness of the presented method．

    Application of Support Vector Machine( SVM) in Prediction of Molten Iron Temperature in Blast Furnace
    CUI Gui-mei，SUN Tong，Zhang Yong
    2013, 20(5):  809-812. 
    Asbtract ( )  
    Related Articles | Metrics

    As a key parameter in blast furnace smelting process，the temperature of molten iron is of importance for smooth operation of
    blast furnace and the energy consumption． This paper studies on the important indicator for heat state of the blast furnace，namely molten
    iron temperature． By taking advantages of both method of K-means clustering and support vector machine( SVM) ，a K-means clustering
    － based SVM model is proposed for predicting the temperature of molten iron． Firstly，the training sample data are divided into m
    classes and m SVM regression prediction models are established accordingly． At the same time，a particle swarm optimization algorithm
    is utilized to optimize the model parameters． Then，m discriminant functions are established to recognize which class the sample data
    belongs to． Finally，the sample data are put into the corresponding class of regression model to predict temperature． Compared to the
    standard SVM － based prediction method，the proposed method predict the molten iron temperature with a higher accuracy．

    Fuzzy Self-tuning PI Control Approach for Freeway On-Ramp Metering
    CHI Rong-hu，YANG Xiu-qin，LI Jian-ying，LIU Xiang-peng
    2013, 20(5):  813-817. 
    Asbtract ( )  
    Related Articles | Metrics

    On-ramp metering is an effective tool for traffic management on freeway networks． In this paper，based on the ordinary differential equation( ODE) model of the ramp system，a new fuzzy self-tuning PI controller for freeway ramp metering is designed． By considering the upstream and downstream traffic flow information sufficiently，the designed PI controller can effectively suppress the influence of the system disturbances． Furthermore，a fuzzy logic is esigned to tune of the PI controller parameters automatically． Compared with both PID and ALINEA approaches，the simulation results illustrate the validity and efficiency of the presented method intensively．

    Building Blocks Design and Implementation of Glareshield for A320 Simulator
    CHEN Jing-jie，XIAO Chen，QIAN Wen-gao
    2013, 20(5):  818-820. 
    Asbtract ( )  
    Related Articles | Metrics

    A building block approach is presented to design Glareshield of a simulator． On the basis of its function categorization，this
    approach aims at designing independent functional blocks through appropriately lowering relative dependence on connections between
    blocks of operating board and control board，realising separation of function and structure，module segmentation and data communication
    between modules． Furthermore，taking communication between blocks as an example，independent communication blocks were designed，
    which effectively prevented frequent occurrence of system crashes due to code disorder in communication． Through experiments
    in applications，it proves that the building block design approach can greatly improve the reliability of the simulator． Furthermore，this
    approach could also be applied in the design of front roof and center control console．

    Dynamic Pricing Model of Perishable Items with Price-dependent Demand
    CAO Xiao-gang，WEN Hui，LI Ji-zi，ZHENG Ben-rong
    2013, 20(5):  821-824. 
    Asbtract ( )  
    Related Articles | Metrics

    The dynamic pricing model of the perishable product with the price-dependent demand using the optimal control theory is established．
    The objective is to maximize the total sales profit within the sale planning horizon． The optimal conditions of the sale price are
    obtained according to the Pontryagin maximum principle． And if the sale price is between the unit purchasing cost of the product and the
    upper limit of the sale price，a lower limit of the optimal sale price and a higher limit of the optimal inventory level at every time point
    of the sale planning horizon are obtained which are both related to the perishable rate and the unit holding cost of the product at every
    time point of the sale planning horizon．

    PSO-BP-PID Control of Ladle Furnace Proportioning System
    OU Qing-li，WU Xing-zhong，OU Da-xian
    2013, 20(5):  825-828. 
    Asbtract ( )  
    Related Articles | Metrics

    In accordance with the control features of material proportioning process of the ladle refining furnace，e. g. ，inertia，time
    lag，non-linearity，a kind of compound control algorithm is proposed based on particle swarm optimization algorithm( PSO) ， error back
    propagation( BP) neural network and proportion integration differentiation( PID) algorithm． The PSO-BP-PID compound algorithm is applied
    in a 150t ladle refining furnace burden weighing control system． The particle swarm optimization algorithm with global optimization
    characteristics improves the convergence of the BP neural network which the initial weights of BP neural network is optimized． The optimized
    BP neural network is then used to adjust PID parameters on-line． The PID controller based on PSO and the BP neural network
    controls real-time the proportioning process of the ladle refining furnace． The simulation and operation experimental results show that the
    control effect of the PSO-BP-PID algorithm is better than the control effect of the traditional PID algorithm． The control system of the ladle
    furnace ingredients based on PSO-BP-PID algorithm can significantly improve the accuracy of ingredients，and effectively solve the
    contradiction between ingredients weighing speed and accuracy．

    The Research of Hybrid Noise Filtering for Images Based on Pulse Coupled Neural Network
    ZHANG Yan-zhu,LI Yuan,LI Xiao-juan
    2013, 20(5):  829-832. 
    Asbtract ( )  
    Related Articles | Metrics

    To the speciality of mixed noise constituted by pulse noise and Gauss noise，we present a comprehensive algorithm in this
    text，which is based on the simplified PCNN model，utilizing several technique specialities of the model，selecting parameters properly，
    and combining with mathematical morphology method，median filtering and wiener filtering． This method performs better than average
    filters and median filters on hybrid noise reduction while retaining edges and detail information of the image． Experiments show that the
    effect of eliminating grey image mixed noise which applying the simplified PCNN eliminating algorithm proposed in this paper is good．
    This algorithm can show a big advantage when in the comparison with other algorithms． This algorithm not only can effectively filter hybrid
    noise but also can excel in real-time tasks because of its reduced computation complexity． With the increase of the image populated
    by blends noise，the advantage is obvious．

    Decoupling Phase Locking Based Control System Simulation of Grid-connected Wind Power
    WU Xin-kai，LIU Yang
    2013, 20(5):  833-836. 
    Asbtract ( )  
    Related Articles | Metrics

    By using the decoupled double synchronous coordinate system software phase locked loop ( DDSRF-SPLL) ，it can detect the
    unbalanced grid voltage of positive sequence component and negative sequence component，and put forward the coordinate transformation
    of the mathematical to establish the grid side of directly-driven permanent wind generator's mathematical model，which includes
    network side PWM inverter control and Voltage phase locked loop． A kind of current decoupling control strategy is proposed． It uses the
    space vector pulse width modulation ( SVPWM) on AC output current control． This method can independently control the output current
    of the active and reactive component，and can make the output current waveform of sine and grid voltage in phase with the same frequency．
    Thus it can greatly reduce the harmonic pollution． It can eliminate the influence of unbalance voltage，and to achieve a precise
    phase-locked output current and gird voltage three-phase grid voltage amplitude imbalance． In this paper，using Matlab /Simulink software
    platform，the simulation proves the validity and feasibility of the control system when the grid stays in balance and unbalance． This
    system improves reliability of wind power grid connection．

    Boundary Control for a Class of Parabolic Distributed Parameter Systems
    WEI Ping，DING Mao，ZUO Xin，LUO Xiong-lin
    2013, 20(5):  837-840. 
    Asbtract ( )  
    Related Articles | Metrics

    Using classical Lie symmetry theory，boundary control for a class of parabolic distributed parameter systems has been studied，
    and the control laws on open loop and closed loop have been designed to control the system reaching the fixed stationary state． By
    means of infinitesimal generators and invariance condition，the analytic control conditions on open loop and closed loop are presented after
    having the classical Lie symmetry of the system，which is expressed by infinitesimal generators． The control purpose can be satisfied
    under the two types of control laws by setting system parameters，initial condition and control purpose ahead． Comparatively，from the
    simulation，the convergence of output error under open loop control is slower than that under closed loop control，and however there are
    overshoot phenomena nearby the intake under closed loop control． The result proposed in the paper can be applied for controlling a class
    of temperature or concentration models with conduction and convention characteristics．

    The Research of Algorithm for Dynamic Network of Power Line Carrier Communications
    LIN Jing-dong，QIN Yu-long，LIAO Xiao-yong
    2013, 20(5):  841-843. 
    Asbtract ( )  
    Related Articles | Metrics

    The uncertainty of the Power carrier communication network makes it unable to form a network，using the general communication
    networking method． To solve this problem，this paper designed a improved genetic algorithm applicable to path optimization． The
    algorithm can rapidly and accurately build global communication network． Firstly，the genetic algorithm is used to all communications
    nodes and communication paths for global searching． Then，when the communication node breaks down，the genetic algorithm will use
    its global optimization characteristics to build communication network． During the network process，Dijkstra algorithm and the thought of
    Graph Traversing algorithm are introduced to overcome the shortcomings of the genetic algorithm，such as，easiness to converge to a local
    optimal solution and small Processing scale． Finally，according to the most optimized reserved principle of The Niching Technique，
    the improved genetic algorithm can get the best network results． Matlab simulation experiments verifies the convergence and feasibility of
    the algorithm． The algorithm improves the efficiency and rapidity of network to meet instantaneous and accuracy requirements of the
    Power carrier communication dynamic network，and has practical value．

    Research on the Control of Doubly － fed Induction Wind Power Generator without Speed Sensor
    LIU Ting，HUANG Shou-dao，DENG Qiu-ling，CHEN Guo-fu，PU Qing-yun，GUO Deng-ta
    2013, 20(5):  844-848. 
    Asbtract ( )  
    Related Articles | Metrics

    The proportional relation of the current of stator and rotor is indirectly used to analyze the relation of the rotor current and rotor
    position observer． By analyzing the simulation results a vector control strategy for doubly － fed induction generator ( DFIG) based on PQ －
    power rotor position observer is proposed． This control strategy overcomes the drawback of incorrect observation in other speed observer
    methods when running at the synchronous speed． The proposed control strategy has wider speed range，and can achieve the control performance
    similar as the control method using speed sensor． Finally，a DFIG experimental system is built up and the experiments are performed．
    The simulation and experimental results have a good agreement verifying the effectiveness of the proposed control method．

    Relative Stability Analysis Method of LTI System with Time Delay
    ZENG Qi-jie，ZHANG Yun，TANG Bin
    2013, 20(5):  849-853. 
    Asbtract ( )  
    Related Articles | Metrics

    Time-delay is frequently encountered in many control problems． The existence of time-delay induces difficulty in stability analysis
    and may thereby lead to oscillations or degraded performance in closed-loop systems． This paper investigates the stability analysis
    of linear time-invariant( LTI) systems with time delay depending upon the solution of the characteristic equation． Not only the absolute
    stability but also the relative stabilities the transient performances are depended on the locations of the characteristic equation roots． The
    existence of time delay transforms the closed-loop characteristic equation into a transcendental equation with an infinite number of roots．
    By investigating the real part and the imaginary part of the transcendental equation，the characteristic equation can be transformed into a
    rotation equation with two vectors related to the system parameters． The characteristic roots on the given region boundaries can be determined
    exactly and concisely． Numerical examples are provided to illustrate the proposed algorithm．

    Dynamic Weapon Target Assignment Method Based on Embedded Markov Chain
    ZHANG Hai-long，SUN Shi-yu
    2013, 20(5):  854-858. 
    Asbtract ( )  
    Related Articles | Metrics

    In this paper，the technical limitations of minimizing resource losing model and maximizing threat model are analyzed via reviewing
    the current research of weapon target assignment ( WTA) problem． To solve the non － real － time problem with the existing
    methods，a dynamic WTA method is proposed which accords with the practical combat． Firstly，to make the allocation model being real
    － time and general，the dynamic input of target is introduced at random． Secondly，aiming at the dynamic random system with target inputs，
    the state of rebirth time is analyzed，and the system is transformed into a Markov process by embedded Markov Chain． Then the
    system state transition probability is resolved． Thirdly，the objective function is constructed，and the target assignment dynamic model is
    established by state transition matrix． Finally，the solution of model is given，and its validity and real － time characteristics are proved．
    The method proposed in this paper refines and complements current weapon target assignment models．

    Robust Fault Tolerant Control for Networked Control System with Variable Sampling Period
    FAN Jin -rong,FANG Hua -jing
    2013, 20(5):  859-863. 
    Asbtract ( )  
    Related Articles | Metrics

    Robust fault tolerant control of networked control system ( NCS) with variable sampling period and time delays was studied in
    this paper． First，a discrete － time model with parameter uncertainties lying inside a polytypic framework whose vertices were determined
    through the Real Jordan form approximation is proposed． Based on the model，an observer was proposed to estimate the fault and guarantee
    the convergence speed of fault estimation． Furthermore，the robust active fault tolerant controller based on dynamic output feedback
    was designed to guarantee the stability of the closed － loop system． A sufficient condition for the existence of controller to guarantee
    the system asymptotically stable is established in terms of linear matrix inequalities ( LMIs) ． When the LMIs have an optimal solution，
    explicit expression of the desired optimal H∞ tolerant fault controller can be determined． Finally，numerical simulation is presented to illustrate
    the effectiveness of the proposed design techniques．

    Hardness Prediction for CAPL Based on Process Average Trajectory
    PENG Jun，WANG Jian-hui，TAN Shuai，WANG Yuan
    2013, 20(5):  864-868. 
    Asbtract ( )  
    Related Articles | Metrics

    The grain of strip steel can be turned to uniform． And the work hardening and inner stress can be eliminated by continuous
    annealing line． So it is the key for improving steel’s mechanical properties． But in a real production process，the mechanism of continuous
    annealing is complicated． The coupling operation parameters could change the characteristics of strip steel，and the detection of steel
    hardness has a long time lag，which brings grate obstacle to improve steel quality． PLS is used to build the relationship between average
    trajectory process and hardness． It can guarantee the safety of production process by realizing hardness prediction and process monitoring
    timely． Simulations in real process shows the feasibility and effectiveness of the proposed method．

    Research on a Seam Tracking System Based on Laser Vision Sensor Measuring
    HE Hong-lin，LEI Xiu-cai，GONG Ye-fei，ZHAO Can
    2013, 20(5):  869-872. 
    Asbtract ( )  
    Related Articles | Metrics

    Aimed to improve the seam tracking precision while welding，this paper proposes a laser vision seam tracking system which
    is composed of a laser vision sensor，a deviation correction controller，two stepping motors and a cross slider． While the tracking system
    runs，the laser vision sensor measures position deviation between the seam gun’s current position and desired position，and the controller
    determine the correcting value，and the motors drive the cross slider to modulate the seam gun’s position and posture so as to offset
    seam tracking error． The prototype of the system was constructed． Seam tracking experiments show that the tracking error can limit to being
    less than 0. 5mm． It is concluded the laser vision seam tracking system exists wide application prospect in precision welding engineering．

    Research on Power Cable On-line Insulation Monitoring for Underground Coalmine
    DONG Ai-hua，LIU Zeng-yin，GENG Xin-lin，WANG Shao-hua
    2013, 20(5):  873-876. 
    Asbtract ( )  
    Related Articles | Metrics

    On the basis of the analysis and comparison of the existing power cable insulation monitoring methods，it designs the online
    monitoring system of the underground power cable insulation approach for the operational characteristics of the underground coalmine cable
    lines． The system uses the low-frequency signal injection method，injecting the low-frequency signal into the cable through the reactor
    neutral point． It constitutes a loop of the low － frequency signal，the cable insulation resistance and the Earth． Under the circumstances
    of injecting certain low-frequency voltage，it can achieve on － line monitoring of the cable insulation，by detecting the value of
    the low-frequency current-line，so the problems of poor reliability and low sensitivity on-line insulation monitoring of the power cable are
    solved better． The experiment shows that this method has a low error and high accuracy in detection; it can monitor not only the single
    cable insulation but also the multiple ones． It can apply to both the main cable circuits and the branch ones．

    Neuro-fuzzy Based PID Cascade Control of Main Steam Temperature of Fire Electrical Engineering Set
    JIA Li，CHAI Zhong-jun
    2013, 20(5):  877-881. 
    Asbtract ( )  
    Related Articles | Metrics

    How to quickly control the main steam temperature to the setpoint is difficult problem in the field of fire power station control．
    Considering the control problem of the main steam temperature of super critical boiler machine set，a neuro-fuzzy model based adaptive
    PID cascade control for the main steam temperature of fire electrical engineering set is proposed in this paper． A neuro-fuzzy
    model for main steam temperature is established by using the information of attemperation water flow，inlet temperature of high temperature
    superheater，main steam flow and the main steam temperature． Then the adaptive PID cascade control of main steam temperature is
    implemented． A PI controller is employed in the inner loop to overcome inner disturbance，which can decrease the influence of the leading
    area＇s differential temperature． Then the single neuron PID controller ( SNAC) is implemented to control the called generalized
    process，which includes PI closed loop and inert segment． This controller is adjusted to eliminate the error between the predicted value
    and the output value． Finally，the effectiveness of this methodology is verified by simulation example．

    The Research of Passenger’s Evacuation in Ships by Using Improved Ant Colony Algorithm
    SHEN Ji-Hong，WANG Kan，LI Pu
    2013, 20(5):  882-886. 
    Asbtract ( )  
    Related Articles | Metrics

     With the background conditions，this paper gives an accurate model to describe the passenger’s evacuation in ships． Also
    an improved ant colony algorithm is given by using a new heuristic function and convergence conditions． The new algorithm can increase
    the influence of social factors and psychological factors in personnel evacuation． The simulation result shows that it can successfully
    solve the problems and it is better than basic ant colony algorithm in both time and efficiency． It can provide a new idea in this kind of
    problems．

    The Research of Sense Pruning for WSD
    XIN Ri-hua
    2013, 20(5):  887-890. 
    Asbtract ( )  
    Related Articles | Metrics

    Word sense disambiguation is one of the first problems in natural language processing system so far． It trys to solve the problem
    of word sense disambiguation in natural language processing by Sense Pruning using HowNet． We proposes that the objective of
    WSD is to reduce the number of plausible meanings of a word as much as possible through“Sense Pruning”． After Sense Pruning，it
    will associate a word with a list of plausible meanings． It would like to keep the truly correct sense of each word on its own meaning list．
    Developing a human-machine mutual word sense tagging system and two set of criteria were used for the evaluation of Sense Pruning algorithm:
    recall rate and reduction of the number of possible meanings of a sentence． Effects of the size of the analytical window and the
    analytical unit were studied．

    Research on Parameter Identification of Overhead Crane Based on Energy Reservation
    LU Xing-long，WANG Liang-yong
    2013, 20(5):  891-895. 
    Asbtract ( )  
    Related Articles | Metrics

    Aiming at solving the problem of poor availability of the physical parameters of a practical overhead crane，this thesis proposes
    a parameter identification method based on energy reservation． It builds up regression equations for identification based on energy
    reservation principle，and then applies non-negative least squares algorithm to deal with data，obtaining the controller design model of overhead
    crane． This thesis has the identification experiments done on the overhead crane experimental system simulating the characteristics
    of the operation of practical overhead crane and gets the mathematical model of the system． On the basis of the mathematical model，
    an LQR controller has been designed to testify the accuracy of the identification results，confirming that the parameter identification
    method can help a lot on control of overhead crane．

    Moral Hazard and Incentive Mechanism of Virtual Enterprise with Fairness Preference
    CHEN Ke-gui，HUANG Min，WANG Xing -wei
    2013, 20(5):  896-899. 
    Asbtract ( )  
    Related Articles | Metrics

    To ensure virtual enterprise ( VE) reaches the desired goals，the owner should design effective mechanisms to avoid moral
    hazard． In view of the VE exists principal agent relationship between the owner and the partner，we incorporate the partner’s fairness
    preferences psychology and design an effective incentive mechanism considering the partner’s fairness concern to prevent the moral
    hazard problem，and compared to the traditional principal agent model． Analysis results show that the fairness preference has changed
    some of the conclusions of the traditional principal agent model that influences the effort level and the revenue sharing． The owner
    should try to choose the partners with lower intensity fairness preferences psychology to avoid moral hazard in order to increase its own
    profit．

    Passive Scattering Transform Bilateral Teleoperation for an Internet － Based Mobile Robot
    CHEN Yi -bin，XI Ning，LI Hong-yi
    2013, 20(5):  900-905. 
    Asbtract ( )  
    Related Articles | Metrics

    The random time delay brings great challenges to the controller design for the Internet － based teleoperation system，the worst
    case is that it can destabilize the Internet － based teleoperation system． First it gives a brief historical preview of bilateral passive control
    theory and the wave variable control approach，and then a passive scattering transform method，extending the passive bilateral control
    method to the Internet － based random time delay teleoperation system，is advanced to guarantee the teleoperation system’s stability
    with any non － symmetric random network time delay． Finally，a virtual master － slave manipulator bilateral control scheme is designed
    for mobile robot teleoperation based on the passive scattering transformation method，and simulations are carried out to verify the results
    at the end of this paper．

    The Design of Control Law of Transition Zone of Missile Based on Gauss Pseudospectral Method
    WANG Li-xin，LENG Shan，WANG Jian-hua
    2013, 20(5):  906-909. 
    Asbtract ( )  
    Related Articles | Metrics

    Aiming at the control problem of glide stage to cruise stage，considering rotation of the Earth and stamping constraint and initial
    state constraint of the cruise stage，control law design model has been build． Optimal control problem have been translated to nonlinear
    programming problem Using Gauss pseudospectral methods． Nonlinear programming problem has been solved by SNOPT． The simulation
    results show that Gauss pseudospectral methods can solve optimal control law problems of glide stage to cruise stage．

    Hovering Control for Quadrotor Unmanned Helicopter Based on Fuzzy Self-tuning PID Algorithm
    LI Yi-bo，SONG Shu-xi
    2013, 20(5):  910-914. 
    Asbtract ( )  
    Related Articles | Metrics

    Quadrotor Unmanned Helicopter ( QUH) is a kind of under － actuated system with multiple inputs and strong coupling． It
    has a broad application prospect，such as aerial photography，archaeology，patrolling border，anti － terrorism investigation． Dynamical
    model can be established according to Euler＇s theorem and Newton＇s law，considering the effect of air resistance and rotating torque． A
    dual － loop control system is designed based PID algorithm，and then another system is designed based on fuzzy self － tuning PID controller．
    Simulation results of two controllers reveal that the QUH can arrive at the specified position and keep hovering and control effects
    of fuzzy self － tuning PID controller are better than that of classic PID in the aspect of response time and stability．

    Quadrotor UAV Robust Adaptive Attitude Control
    ZHEN Hong-tao，QI Xiao-hui，XIA Ming-qi，SU Li-Jun
    2013, 20(5):  915-919. 
    Asbtract ( )  
    Related Articles | Metrics

    The attitude control is the key of the automatic flight control for quadrotor UAV． In order to improve the robustness of quadrotor
    UAV for various uncertainties，a robust adaptive backstepping controller is designed． The whole attitude kinematical model is obtained
    and translated into a MIMO nonlinear system with generalized uncertainty． Because the design feature of the system is strict feedback，
    the backstepping controller is designed． A robust adaptive function is designed to counteract the influence of the uncertainties，
    which include external disturbance and interior parameters perturbation． The nonlinear tracking differentiator is introduced to estimate
    the differential signal of the virtual control law and to reduce the“computer explosion”problem which is ubiquitous in the backtepping
    controller． The closed － loop system is proved to be stable and converge exponentially through constructing Lyapunov function． Simulation
    results are presented to corroborate the effectiveness and robustness of the proposed control strategy．

    Research on Disturbance in Nearspace Vehicle Longitudinal Trajectory System
    HE Nai-bao，GAO Qian，Luo Yin-sheng
    2013, 20(5):  920-922. 
    Asbtract ( )  
    Related Articles | Metrics

    Considering the severe changes of aero － dynamic parameters and susceptibility on the external disturbances of nearspace vehicle
    ( NSV) ，a backstepping control strategy with robust adaptive dynamic surface is proposed in this paper for the disturbance problem in the NSV
    longitudinal trajectory system during the hypersonic process． Firstly，the complex nonlinear longitudinal dynamic model is transformed into
    nonlinear non － affine model by using the input － output feedback linearization method． Then，the“computer explosion“in the computation
    procedures for derivatives is avoided with the estimation of the virtual control law in one － order low pass filter． The robustness item in the virtual
    controller combined with approximation capability of neural network is used to eliminate the parameter uncertainties and external disturbances
    in NSV． The simulation results show the improved robustness in this method with reduced complexity．

    Research on the Aircraft Terrain Avoidance Strategy Based on the Interacting Multiple Models
    GENG Jian-zhong，Wu Hu-zi，DUAN Zhuo-yi
    2013, 20(5):  923-928. 
    Asbtract ( )  
    Related Articles | Metrics

    Since the disadvantages and limitation of anti-collision system with radar in aircraft ( ACSR-anti-collision system with radar
    in aircraft) ，the terrain avoidance strategy was proposed，which adopted the virtual radar to substitute the airborne radar system to solve
    the problem of the terrain anti-collision． According to characteristics of aircraft motion，uniform motion model，uniformly accelerated
    motion model and the current statistic model were established，which are suitable for fast and accurate prediction． The principle of the
    interacting multiple model and Kalman filtering were adopted to predict the aircraft flight conditions in real time which were used to
    match the airborne terrain database to avoid crash． The prediction arithmetic was testified by simulation，and the results show that the
    prediction time has important effect on deviation． But the warning level can be determined according to the forecast time． The research
    demonstrated that terrain avoidance is much more advanced than ACSR，and it can replace ACSR．

    Passivity-Based Control for SPMSM Based on Unified PCHD Modeling
    HOU Li-min，SONG Shao-lou，WANG Wei
    2013, 20(5):  929-933. 
    Asbtract ( )  
    Related Articles | Metrics

    In view of the nonlinear characteristics of the SPMSM drive system，the unified PCHD modeling and speed control of PMSM
    is presented based on the interconnection and damping assignment of energy-shaping method and port-controlled Hamiltonian systems
    with dissipation( PCHD) theory，to obtain high performance of the speed control system． First，from an energy-balancing point of view，
    uncertain system unified PCHD modeling is established including the inverter，SPMSM with iron losses and mechanical load． And then，
    the passive controller of the SPMSM drive system is designed，and the nonlinear disturbance caused by the inverter is compensated using
    the extended state observer． Finally，speed regulator is designed by using ADRC in order to get the desired q axis current，both the design
    and the implementation of the controller becomes simpler and easier． The simulation results show that the proposed method can ensure
    global stability，strong robustness． The system achieves a satisfactory dynamic and static performance．

    Gray Neural Network Algorithm Improved by Genetic Algorithm
    LI Guo-yong，YAN Fang，GUO Xiao-feng
    2013, 20(5):  934-937. 
    Asbtract ( )  
    Related Articles | Metrics

    BP algorithm usually has slow convergence speed and is easy to fall into local minimum value． On the basis of the analysis
    and study for the domestic market of air conditioning order． This article proposes a method of the model parameters of grey neural network
    optimized by genetic algorithm． By utilizing the property of gray model that the randomness of data can be reduced and the strong
    nonlinearity of neural network，the method establishes a non-linear prediction model for air conditioning demand，and the genetic algorithm
    is used to optimize it so as to improve the accuracy of forecasting and speed up the degree of convergence． Simulation results indicate
    that the algorithm can better solve the problem of air conditioner order forecasting and can be widely apply to similar prediction．

    Study on Advance － Booking Discount Strategy in a Two － Level Supply Chain with Multi － Loss － Averse Retailers
    HU Zhi-jun，CHANG Jia-jia，XIANG Shu-wen
    2013, 20(5):  938-942. 
    Asbtract ( )  
    Related Articles | Metrics

    The classical newsvendor model ( CNM) is often used to study the supply chain coordinating problem with perishable products
    in single period，and only one order is permitted in the CNM，which is inappropriate in fact． However，for some perishable products
    with the special consumed time，such as the moon － cake for Middle － Autumn Festival，etc． ，the manufacture for these items provide
    a price discount for advanced booking in order to reduce inventory level． This paper considered a two － stage supply chain composed
    of a risk － neutral supplier and multiple competing loss － averse retailers，and investigated the combined impact of the competition
    and retailer’s loss aversion attitude on the decision － making behavior of retailer and the coordination of supply chain within the
    advanced － booking discount contract． Based on game theory，it shows that in this supply chain game，there exists a unique symmetric
    pure Nash equilibrium，and the optimal total order quantity increases as the degree of competition increases but decreases as the loss aversion
    increases． Moreover it is found that，advance － booking discount contract can coordinate the supply chain． At last，the effectiveness
    of advanced － booking discount Contract is verified in supply chain by a case study．

    A Modified Differential Evolution Algorithm Based on Hybrid Mutation Strategy for Function Optimization
    QIAO Jun-fei，FU Si-peng，HAN Hong-gui
    2013, 20(5):  943-947. 
    Asbtract ( )  
    Related Articles | Metrics

    The traditional mutation strategy of differential evolution algorithm can not reach a good balance between the global search
    and the local search and the operators are constant． The differential evolution algorithm leads to premature convergence and the low
    search efficiency． Based on analysis of the performance of the optimization strategies，a hybrid mutation strategy is proposed in this paper．
    The scheme attempts to balance the exploration and exploitation abilities． In this way，emphasis is laid on the global search at the
    beginning，which results in maintaining the diversity of population． Later，contribution from the local search increases in order to converge
    to the optimal faster． Meanwhile，the random normal scaling factor F and the time － varying crossover probability factor CR are
    used synchronously to improve the performance of DE． Finally，the modified differential evolution algorithm is tested on benchmark
    functions． The simulation results show that the modified algorithm can effectively avoid the premature convergence，as well as modified
    the global convergence ability and the search efficiency remarkably．

    Optimization for Output Feedback Dynamic Surface Control Based on Genetic Algorithm
    HE Lei，SUN Xiu-xia，LI Xiao-dong，DONG Wen-han，YU Xiu-duan
    2013, 20(5):  948-952. 
    Asbtract ( )  
    Related Articles | Metrics

    For a class of uncertain systems with only output available and nonlinearities in the presence of unmeasured state，a state observer
    based on input signal replacement is firstly established by using the neural networks，then，an output feedback adaptive control
    scheme is proposed by employing dynamic surface theory． The controller parameters' range is initially selected by theoretical analysis． It
    is guaranteed that all signals in the closed － loop system are semi － global uniformly ultimately bounded． Parameters optimization strategy
    is proposed by using genetic algorithm． Then the optimal initial input and controller parameters are chosen，so the problem of input
    impulsion is solved and tracking precision is improved．

    Multi-Objective Differential Evolution Algorithm For Reactive Power Optimization
    MA Li-xin，Sun Jin，PENG Hua-kun
    2013, 20(5):  953-956. 
    Asbtract ( )  
    Related Articles | Metrics

    The voltage level to reactive power optimization dispatch and control problem is incorporated． A model of reactive power optimization
    is established based on multi-objective differential evolution，which takes into account of loss minimization，voltage level best
    target． Considering the drawbacks of traditional differential evolution ( DE) algorithm such as premature and slow search speed，a
    strategy of self-adapting parameter improved differential evolution algorithm was proposed and first applied in reactive power optimization
    problem． By adjusting the mutation F and crossover CR during the evolution process，the diversity of population is increased and the
    global search area is expanded，which avoids algorithm into a local optimal solution，at the same time，the convergence speed is accelerated
    later． The simulations are carried out on IEEE-14 bus system，and the results show the validity of the proposed algorithm．

    An Improved DAGSVM Hand Gesture Recognition Approach and Its Applications
    CAI Jun，LI Xiao-juan，ZHANG Yi，LUO Yuan
    2013, 20(5):  957-959. 
    Asbtract ( )  
    Related Articles | Metrics

    On the basis of SVM( Support Vector Machine) multiclass classification，an improved DAGSVM ( Directed Acyclic Graph
    Support Vector Machine) hand gesture recognition approach is put forward． Firstly，depth information of the scene is collected by using
    Kinect sensor and hand region is obtained． Then feature vectors are extracted，which are used to train multiple binary SVM classifiers．
    DAGSVM classifier is constructed using DAG topological structure with trained binary SVM classifiers and its structure sequence is improved．
    Finally，the experimental results proved that the improved DAGSVM could reach higher recognition rate and can be used in the
    control of intelligent wheelchair successfully．

    Dynamic Quantization H∞ Control for Networked Control Systems
    WEN Dan-li，WANG Ke-sheng，CHEN Zhi-xun
    2013, 20(5):  960-965. 
    Asbtract ( )  
    Related Articles | Metrics

    The state feedback H∞ control problem for networked control systems with quantization and random packet dropouts is discussed．
    The random packet dropouts from the sensor to the controller and from the controller to the actuator are considered． The quantizer
    considered here is dynamic． The state feedback H∞ controller can be constructed via solving a linear matrix inequality． A quantized
    H∞ control strategy is derived，with a condition on the quantization range and the error bound satisfied，such that the closed － loop system
    with quantization and random delays exponentially mean － square stable and with a prescribed H∞ performance bound． An example
    is presented to illustrate the effectiveness of the proposed method．

    Fast IF Automatic Gain Control System Based on FPGA
    ZHANG Chun-jie，TAN Zhen-wei,LI Na
    2013, 20(5):  966-969. 
    Asbtract ( )  
    Related Articles | Metrics

    In order to meet the needs of the system dynamic range and response time，this paper proposed a FPGA － based rapid IF automatic
    gain control ( AGC) system． First，computer simulation is carryed out using Quartus II simulation to verify the timing and logic
    functions of the system algorithm． And then the design and implementation of the system hardware are completed． Finally，the paper realizes
    a control module inside the FPGA，up to 60 dB of dynamic range control． The validation of the logic simulation software and testing
    of the hardware circuit proved that the response of the system is fast and has high control accuracy，and systems have achieved better
    results in the actual radar receiver，and the proposed method increases the dynamic range of the receiver to improve the performance
    of the radar system．

    Design and Development of the High -speed Data Acquisition System Based on FPGA
    GUAN Shou-ping，YOU Fu-qiang，DONG Guo-wei
    2013, 20(5):  970-975. 
    Asbtract ( )  
    Related Articles | Metrics

    The construction and techno － realization of high － speed data acquisition system are presented． The FPGA is adopted to realize
    the design of the hardware，which includes analog signals filtering plastic circuit，high － speed AD interface circuit，USB interface
    circuit． The system application software design is also analyzed in detailed，which includes FPGA program design，USB firmware program，
    upper computer application software，etc． The experimental results show the feasibility of the designed method．

    Robustness of Sampled-Data Control Systems with LTI Hold Functions
    LI Xia-yu，JIN Hui-liang，DONG Sui-rong，ZHONG Qing-chang
    2013, 20(5):  976-979. 
    Asbtract ( )  
    Related Articles | Metrics

    This paper extended Bernstein and Hollot's robust stability test to linear time-invariant ( LTI) uncertain sampled-data control
    systems． Unlike that of the most previous works，it directly uses the data of the continuous-time plant and therefore it is expected to be
    less conservative． This paper uses exponential-like structure construct an upper bound on the standard quadratic Lyapunov function．
    This upper bound is independent of the uncertain parameters but a free scalar parameter which is artificially introduced to reduce the
    conservativeness of the upper bound． This paper gives out a reliable numerical algorithm． And then this algorithm is improved so that it
    can be used to check the robust stability condition for system with an arbitrary GSHF．

    Leader /Follower Formation Control of Underactuated Surface Ships
    LIU Yang，LIU Mei-jie
    2013, 20(5):  980-983. 
    Asbtract ( )  
    Related Articles | Metrics

    The formation control for underactuated surface ships with 3 degree － of － freedom is investigated，and the shape tracking
    controllers based on Leader /Follower method are developed． The ship is controlled respective，when the system received the shape-command．
    The Leader tracked the shape-command directly，and the Followers tracked the designed trajectory，which is designed by the
    shape-command and the state of the Leader． For the design of tracking control，firstly，reference tracking path and reference forward
    speed are designed based on desired formation shape． Secondly，path tracking controller and speed tracking controller are constructed by
    nonlinear control theory and Lyapunov theory． Finally，the shape tracking error of the follower is uniformly ultimately bounded． Numerical
    simulations show the system can tracking any curves． The results validate the effectiveness of proposed controller．

    Modeling and Optimization of Resources Management of Construction Programme Based on HTCPN
    LI Hai-ling，LIU Ke-jian，TAO Xue-ming
    2013, 20(5):  984-989. 
    Asbtract ( )  
    Related Articles | Metrics

    Resource conflict between the project caused by the limited resources is an important factor affecting the construction period
    and benefits of the construction programme． The building of an accurate model which can describe the information about resource management，
    such as relations among tasks，resource requirements and task duration and so on is the key to the process management and
    optimal allocation of resources for implementation stage of construction programme． Resource model for implementation stage of construction
    programme was defined based on HTCPN by analyzing the resource characteristics of non － depletable resources and the modeling
    requirements for implementation stage of construction programme． The model can accurately describe the whole process of programme，
    and also can find resource conflict，analyze the construction period and choose the optimal resource planning by simulation． With CPN
    Tools simulation platform，taking an example of a construction programme，the authors built its resource model and verified the correctness
    and effectiveness of the model．

    Performance Analysis for Operational Optimal Control for Complex Industrial Processes – the Square Impact Principle
    2013, 20(6):  991-995. 
    Asbtract ( )  
    Related Articles | Metrics

    The operation control for complex industrial processes consists of two layer – loop control layer and operational control layer. The former aims at achieving the required loop control for each production unit along production line whilst the later optimizes the set-points to the control loops so that certain performance indexes (such as product quality and energy cost) is optimized when the closed loop controlled variables follow their set-points well. This paper presents a novel method that can be used to analyze the performance deterioration of the optimized operational control, where the impact of tracking errors of loop control to the optimized performance is quantitatively formulated when the tracking errors are small. It has been shown that loop tracking errors would generally deteriorate the optimized performance in a quadratic way – leading to the establishment of the square impact principle (SIP). Moreover, it has been shown that the production infrastructure will also affect the deterioration of the optimized performance. Formulation on the analysis on the flat robustness (FR) and randomness of the optimized performance indexes will also be made and several issues on the future studies are listed.

    A New Pairing Method Based on Multivariable State Feedback Predictive Control
    2013, 20(6):  996-999. 
    Asbtract ( )  
    References | Related Articles | Metrics

    For the multivariable control system, interaction analysis and variable pairing are the first step for the control system design. In order to handle the problem that RGA do not reflect the dynamic characteristic among loops, all kinds of improved dynamic relative gain array are presented. The paper presents a new variable pairing method based on multivariable state feedback model predictive control. It can fully reflect the dynamic and stead-state information about control process. Through the optimization of the prediction horizon, the correlation index array can be identified. Combining the correlation index array and steady state array, the final pairing array is defined. Several cases and the comparisons with the existing methods indicate that the proposed method is a useful tool to give the best pairing scheme.

    Study on On-line Self-tuning PSS Based on the Parameters Adjusted by a Fuzzy Neural Network
    2013, 20(6):  1000-1004. 
    Asbtract ( )  
    Related Articles | Metrics

    To improve the static and transient stability of disturbances with all scales in power system, this paper provides a control strategy of an online self-turning stabilizer based on the parameters adjusted by a fuzzy neural network. Compared with the conventional fuzzy stabilizers, the strategy adds a fuzzy neural network parameter adjuster which stores the fuzzy rules in the neural network combing a qualitative description and a quantitative numerical calculation. The adjuster makes full use of the neural-network’s associative memory and parallel processing ability, adjusting the conventional fuzzy stabilizers’ parameters of quantitative factors and scale factors on line quickly and dynamically. According to the experiment, compared with IEEE PSS2B and conventional fuzzy stabilizers, the proposed control strategy can increase the damping of the power system effectively, strengthen the ability to withstand different scales of disturbances, with strong adaptability and robustness, and improve the static and transient stability of the power system greatly. The proportional control strategy has a broad prospect in industrial application.

    Multifunctional data acquisition system for intelligent autonomous mobile robot
    2013, 20(6):  1005. 
    Asbtract ( )  
    Related Articles | Metrics

      Abstract: An embedded multifunctional data acquisition system was designed for intelligent autonomous mobile robot to detect its operating environment and status information. The system contains four acquisition circuits for ultrasonic sensors, six signal collection circuits that support the collection for both voltage signal from 0V to 5V and current signal from 4mA to 20ｍA, eight digital signal output channels, eight digital signal input channels, and the data acquisition system interface data with other device via PC/104 bus. This paper introduced the composition of the data acquisition system, detailed designed the bus interface circuit,ultrasonic detection circuit, the digital signal input-output circuit, and the analog signal detection circuit for the system. With the characteristics of simple structure and good practicability, the system has a good application in the detecting of the operating environment and status information of intelligent autonomous mobile robot.

    Adaptive learning control based on least squares algorithm with a forgetting factor
    2013, 20(6):  1010. 
    Asbtract ( )  
    Related Articles | Metrics

    A Parameter adaptive iterative learning control scheme for trajectory tracking in a finite duration is proposed for a class of discrete nonlinear system with unknown time-varying parameters and linearly growing condition. It discusses the convergence performance of the algorithm and improves convergence rate using forgetting factor. By using least squares algorithm with a forgetting factor in discrete adaptive control, a new parameter adaptive and controlling law is constructed in iterative field. Pointwise convergence in time domain and gradual convergence in iterative domain are proved with Lyapunov-like function. Two simulation examples are provided to validate the efficacy of the proposed parameter adaptive law and controller.

    A  License Plate Tilt Correction Algorithm Combined Hough and Radon Transform
    2013, 20(6):  1014. 
    Asbtract ( )  
    Related Articles | Metrics

    For the problems that Hough transform can not correct the license plate without frame border and Radon transform is computation-intensive and time-consuming, a fast algorithm combined Hough transform and Radon transform for license plate tilt correction was proposed. By setting effective detection areas and making full use of Krisch to get the horizontal edge, this method can correct both the rim license plates and the rimless ones fast and effectively.  Selected 200 artificial slanted pictures to verify the accuracy of angle inclination got from the algorithm, and selected 400 natural slanted pictures to compare the speed and accuracy of the three algorithms, namely Hough, Radon and the method in this paper. Performed in Matlab platform with the angle ranged in [-20°,20°], the average execution time of the proposed algorithm is 0.38s and its accuracy achieves more than 90%. Experimental results show the algorithm is fast, accurate and robust.

    Vector Control of Direct-driven PMSG Wind Turbine Based on Improved SMO
    2013, 20(6):  1018. 
    Asbtract ( )  
    Related Articles | Metrics

    Based on the mathematical model of direct-driven wind turbine with permanent synchronous generator(D-PMSG) the sliding mode observer(SMO) is built to achieve estimating rotor position and speed and its improvement. Saturation function to replace the discontinuous switching function to weaken the SMO inherent chattering defects. In addition, for the traditional method of selection of low-pass filter to extract continuous signal caused by the phase delay problem, this paper constructs the EMF observer to replace the low-pass filter is directly extracted from the back EMF signal, eliminated the phase compensation and improved the estimation accuracy. Eventually established a vector control system of direct-driven PMSG wind turbine based on improved SMO. By comparing the simulation analysis，the results that the system can accurately estimate the rotor position and speed, and has a good dynamic and static performance. And further experiments to verify the feasibility and effectiveness of the program, with the value of engineering applications.

    Study of DTC System Based on Fuzzy Control
    2013, 20(6):  1023. 
    Asbtract ( )  
    Related Articles | Metrics

    The same space voltage vector is chosen by Bang-Bang control in the traditional Direct Torque Control (DTC) system in the case of both big and small error. To solve the problem, it is proposed that the hysteresis and voltage vector table are replaced by a fuzzy controller, so as to increased torque dynamic response speed and reduce the flux and torque ripple. Fuzzy logic is introduced. The errors on the torque and the stator flux linkage are fuzzy classified and the space voltage vector can be reasonable obtained according to the errors .Through fuzzy logic calculate, suitable space voltage vector is obtained to control induction motor. A design method of the fuzzy controller is presented particularly. Hardware and software design of the fuzzy direct torque control system is given. The results of simulation indicated that the response of the system is quicker when the motor start or the rotate speed breaks , torque and flux ripple is smaller, the dynamic and static performance is improved. There are good results in the occasions that require fast dynamic torque response.

    Predictive control strategy for LPV systems based on offline state observer
    2013, 20(6):  1027. 
    Asbtract ( )  
    Related Articles | Metrics

    Consider a constrained LPV system with polytopic description. An offline design of state observer is proposed when the system state cannot be observed. And the new self-tuning system constructed by state observer error is proved to be robust stable, which guarantees the output of the observer can converge to the true sate value. After that, the parameter dependent Lyapunov function (PDLF) is introduced to obtain poly-quadratically stable control laws by solving the min-max optimization problem with infinite horizon performance cost. And the output feedback control law can guarantee the feasibility and stability of the computational paradigms. Compared with the traditional strategy, the offline design method of observer can greatly reduce the online computation and the utilizing of PDLF can obtain the less conservative condition for the LPV systems. And at last, the simulation results show the effectiveness of the proposed method.

    Design of High-speed Data Acquisition Device Based on DSP
    2013, 20(6):  1032. 
    Asbtract ( )  
    Related Articles | Metrics

    In order to satisfy the high speed and high accuracy request of the X-ray angle sorter, high-speed data acquisition system based on the DSP has been developed which includes X-ray diffraction signal recuperation module, high-speed data sampling and process module and high-speed USB communication module. Signal recuperation module amplifying and filtering the X-ray diffraction signal, the DSP board carrying out high-speed data acquisition and processing for the analog signal, acquisition the signal of photoelectric encode, and transmitting the collected data to the host computer through USB interface. The system application software design is also analyzed in detailed. Furthermore, in order to get the high precision, The separated the FIR algorithm has been embedded to the DSP procedure for filtering data. The experimental results show the feasibility of the designed method.

    Linear Time-invariant Disturbance Observer Feedforward Control for Nonlinear System
    2013, 20(6):  1037. 
    Asbtract ( )  
    Related Articles | Metrics

    It presents a feedforward control strategy based on linear time-invariant disturbance observer for nonlinear controlled objects. At first, choose a linear time-invariant model as target model which have a desired dynamics. And then describe the non-linear properties of the controlled object as an equivalent input disturbance variable of the target model, which can be extended as state variables, so that the target model with the disturbance becomes the substituting model of the controlled object. Thirdly, design an observer of the substitute model to get the estimated value of the disturbance variables. Finally, a feedforward control can counteract the influence of the disturbance on the controlled object. The design theories of this method are confined within the architecture of linear system theory, and independent of the mathematical model of the controlled objects. Particularly, the controller is without any nonlinear part. In circumstances of reversible controlled object, the existence theorem of the substituting model is proved. At last, for the identical discrete time controlled object, comparative simulation research is performed between this control method and a nonlinear internal model control based on support vector machine ?th-order inverse system method. The simulation results indicate that the method proposed in this paper is better in linearization, anti-disturbance capability and system robustness.

    Application of Active Disturbance Rejection Controller in Polypropylene Reactor
    2013, 20(6):  1042. 
    Asbtract ( )  
    Related Articles | Metrics

    Affected by the internal exothermic reaction and the entrance temperature, etc, the polypropylene production process has the characteristics of time-delay and strong inertial, based on discrete auto disturbance rejection control, this paper use tracking differentiator and extended state observer to arrange the transition process and estimate system disturbance rationally, then design a non-linear error feedback control law by the error signal, realize the temperature control of polypropylene reaction axe. At last with the MPCE experiment device and SIMATIC PCS 7 controller, temperature control experiment under disturbance or variable load is studied, the results show system with ADRC ensures very good robustness and adaptability under different conditions, and has better dynamic performance than classic PID in the same operation conditions.

    Orientation Estimation Method for Mobile Robot in Urban Area
    2013, 20(6):  1045. 
    Asbtract ( )  
    Related Articles | Metrics

    To improve the self-navigation ability of mobile robots, an optimal robot orientation estimation method in urban areas is proposed. This method is based on the vertical vanishing point in one view and the horizontal vanishing point correspondences across two views. To obtain an optimal estimation result, an error-aware vanishing point estimation method is developed, leading to a minimum variance solution. By analyzing the error propagation in computing vanishing point, we convert the minimum variance estimation problem to a convex optimization problem, which is well studied in operations research. An orthogonality check is proposed for each candidate horizontal vanishing point. Then, a vanishing point matching method is developed to find the correspondences. Some physical experiments are carried out to validate the accuracy and time-efficiency of our method.

    Improved neural network PID controller of joint robots
    2013, 20(6):  1052. 
    Asbtract ( )  
    Related Articles | Metrics

    Aiming at the rapid trajectory tracking control with the modeling error and uncertain disturbance problem of the joint robot, this paper presents a design of the improved neural network-PID controller. The architecture employs dual-controller mode. Through studying the PID controller’s input and output characteristics the neural network can compensate the modeling errors and uncertain disturbance of the joint robot rapidly, and using the LSM and the input and output characteristics of the converged neural network optimize the control parameters of PID controller can weaken the effect of modeling errors on the trajectory tracking control. The controller is stable in the Lyapunov sense. In the paper, we have a simulation experiment taking the two linked manipulator as the plant. Finally, the superiority of this design is demonstrated through the experimental results.

    Robust Adaptive Control for a class of Nonlinear Systems Based on Support Vector Regression
    2013, 20(6):  1055. 
    Asbtract ( )  
    Related Articles | Metrics

    To solve the problem that nonlinear dynamic inverse method is relatively dependent on the accurate system model and easily affected by inverse error, a nonlinear robust adaptive controller design using Squares Support Regression (SVR) is proposed in this paper，in which SVR is used to identify inverse model of the controlled system and construct adaptive compensation term to eliminate the inverse error caused by uncertain factors, such as inverse model error or disturbances, and so on. This could make the system outputs track the outputs of the reference model rapidly and accurately. The updating rule of SVR parameters is derived, and the stability of the nonlinear system is proved by Lyapunov stability theory. Furthermore, the simulation results of a typical nonlinear model show the feasibility and robustness on solving a class of nonlinear problems of the proposed method.

    Research on Capacity Allocation with Random Demand and Private Information
    2013, 20(6):  1060. 
    Asbtract ( )  
    Related Articles | Metrics

    Capacity allocation strategy of a single facility with random demand and private information, in which the earning per unit of each organization as well as the manufacturing capability of facility are private and the demand of each organization is both private and random, is investigated in this paper. According to the information distribution, the whole problem is decomposed into the facility problem and organization problems whose corresponding stochastic programming models are also given. A negotiation-based method (between the facility and organizations) is proposed to solve the capacity allocation problem. First, the proposed stochastic programming models are equivalently clarified to be parametric programming models, and then parameters design of the negotiation mechanism is performed by Lagrangian relaxation and Taylor series expansion. Further, a distributed deflected sub-gradient method is derived to update Lagrangian multipliers, and in the end the solution algorithm to the capacity allocation problem of a single facility with random demand and private information is given. Finally, numerical examples are employed to analyze the effect of some important parameters on capacity allocation results and demonstrate the efficiency of the proposed method.


    SIMULINK Realization for Fractional order Transfer Function
    2013, 20(6):  1066. 
    Asbtract ( )  
    Related Articles | Metrics

    The dynamic system can be more accurately described by fractional-order differential equation due to the ‘unlimited memory’ principle of fractional-order calculus. Unlike the analysis and simulation of integral-order system which are frequently completed in the SIMULINK environment, the same procession for fractional-order systems are mainly realized in MATLAB workspace at present as the absence of corresponding SIMULINK blocks. In this paper, a block was designed which can display fractional-order transfer function, thus fractional-order system can be analyzed in the SIMULINK environment based on fractional-order calculus theory and SIMULINK mask technology. This block is used as convenient and intuitionistic as the integral-order one. By engineering application, it is validated that the designed block is more useful for the design and analysis of fractional-order system.

    Research on Synchronous Traction Motor Direct Torque Control of High-Speed Train
    2013, 20(6):  1070. 
    Asbtract ( )  
    Related Articles | Metrics

    As the important part of high-speed the EMU traction drive systems, the traction motors provide the most direct impetus to the EMU. Synchronous machine has small volume, light weight, high power factor characteristic, to adapt to the needs of the running of the actual high-speed train is the new generation high speed train traction motor. This paper introduce a direct torque control strategy, the synchronous motor in traction, constant speed and braking mode control technology, and in the train network control system framework, based on the Rt - lab system for the real-time simulation research. The results show that the method possesses a torque response is rapid and the accuracy is high, has the practical application potential.

    Grey extra-deleting control of non-minimum phase systems
    2013, 20(6):  1074. 
    Asbtract ( )  
    Related Articles | Metrics

    Non-minimum phase systems (NMPS) existed widely in engineering field such as electrical power engineering and space engineering. Because there are zero, pole points or delay links of the system transfer function in the right of complex plane, the accuracy of traditional control method is poor. Grey extra-deleting control theory is applied to design the controller of NMPSs. An expected system which has good performance is designed and compared with the original system to find out the excess, and then extra-deleting feedback is applied. The feedback can change the system transfer function and offset or weaken the excess which deteriorate system performance. The grey extra-deleting controllers are designed for some NMPSs and are studied compared with classical PID controllers. Simulation results indicate that the proposed controller can improve the performance of the system significantly and can solve the problem that non-minimum phase system is difficult to control.

    An Adaptive Harmonic Detection Algorithm with Momentum Term
    2013, 20(6):  1077. 
    Asbtract ( )  
    Related Articles | Metrics

    The harmonic current detection method based on adaptive noise cancellation principle has been researched extensively and proved to be feasible. Invariable step-size Least Mean Square adaptive algorithm can't solve the contradiction between convergence speed and steady-state error, this paper presents a variable step-size adaptive harmonic detection algorithm with momentum term, which uses the momentum term to speed up the convergence of weights and uses the autocorrelation estimates of the current and previous error signal to adjust step-size iteration. This algorithm has significant enhancement of harmonic detection in real time and accuracy, and good engineering application prospects because of the small calculation quantity and easy realization. The simulation results verify the effectiveness of the algorithm.

    Study for Sequential Robust State Estimation under Hybrid Measurements
    2013, 20(6):  1084. 
    Asbtract ( )  
    Related Articles | Metrics

    Most power system dynamic state estimation algorithms under hybrid measurements assume that the information can be available at the same time and rarely consider the impact of bad data on state estimation. Aiming at the problems above and taking full advantage of hybrid measurements, a sequential robust dynamic state estimation is proposed based on the analysis of the SCADA estimation time window of the mixed-measure system. Firstly, the algorithm fusions the phasor measurement unit(PMU） measurements sampling at the same time and then the supervisory control and data acquisition(SCADA) measurements are taken into estimation in sequential of arrival time. Then the cost function is calculated. A set of SCADA/PMU measurements is formed and used for state estimation via extended Kalman filter(EKF) if the cost function exceeds a threshold The algorithm can make good use of utilization of the estimation center, reduce the impact of measurement outliers on the state estimation and improve state estimation real-time and accuracy. Finally, simulations on an IEEE 14-bus test system demonstrate the effectiveness and superiority of the proposed algorithm.

    Design and implementation of an intelligent controller of motorcycle
    2013, 20(6):  1088. 
    Asbtract ( )  
    Related Articles | Metrics

    This study is dedicated to the design of an intelligent controller of motorcycle which consists of digital igniter, remote data transceiver module, Passive Keyless Entry module and so on. It can help to increase the engine power, economy and improve the pollution emissions and fuel efficiency, and make the motorcycle achieve a better performance of anti-theft. In order to reduce the oil consumption and exhaust nitrogen oxide efficiently, this paper introduces the accurate matching approach about best ignition time and best ignition pre-angle with speed of engine, applies the digital igniter to control the ignition pre-angle accurately, and balances the engine’s power and oil consumption. We utilize the Passive Keyless Entry module to verify the ID of motorcycle driver, locate the motorcycle by GPS remotely, get the current Chinese address through a search algorithm. It will be more flexible for users to supervise their motorcycle by acquiring the motorcycle’s localization in multi-ways. The experiment results indicate that this controller can locate the motorcycle precisely, the real-time monitoring system is robust, and the anti-theft device is available.

    Weak Stochastic Asymptotic Stability of One Single Machine Infinite Bus System
    2013, 20(6):  1094. 
    Asbtract ( )  
    Related Articles | Metrics

    With the expansion of interconnected power grid, the influence of random factors on power system stability is becoming increasing prominent, and the stochastic stability of power system has become an important research subject. On the basis of the analyses of the existing research work, the purpose of this paper is to discuss weak stochastic asymptotic stability of original stochastic system by using of the stability of its truncation system. Firstly the weak stochastic asymptotic stability theorem is proved in probability. And taking the power fluctuation as random excitation, nonlinear stochastic differential equations model of one single machine infinite bus (OMIB) system is constructed. Then the weak stochastic asymptotic stability of OMIB system under small random excitation is verified by the Lyapunov function cited from reference [2]. Finally the paper gave corresponding conclusions.

    Sliding Mode AQM Algorithm for Internet with Uncertainties and Time Delay
    2013, 20(6):  1098. 
    Asbtract ( )  
    Related Articles | Metrics

    In order to solve the congestion phenomenon in Internet, a sliding mode active queue management(AQM) algorithm is proposed. Considering the effect of uncertainty and time-varying delay factors in Internet, an asymptotically stable sliding surface is designed by linear matrix inequality(LMI) based on the Internet congestion control model. It can effectively overcome the effect of these time-varying factors. The controller is designed by the way of reaching law, which can effectively constrain the oscillation of the queue length in router. Simulation contrasts demonstrate that the proposed algorithm possesses better stability and robustness, and it can adapt to the time-varying Internet environment. An application effect of the proposed sliding mode AQM algorithm in a large electric power enterprise remote monitoring and control network is given.

    Ball Mill Load Condition Recognition Model Based on Regularized Stochastic Configuration Networks

    ZHAO Li-jie, ZOU Shi-da, GUO Shuo, HUANG Ming-zhong
    2020, 27(1):  1-7. 
    Asbtract ( )  
    Related Articles | Metrics
    Stochastic configuration network (SCN) is a universal approximator which can be automatically and quickly constructed under the supervision mechanism with inequality constraint. It has potential advantages in the field of large data modeling. In order to enhance the accuracy and stability of the model prediction, a stochastic configuration network model with L2 norm regularization (L2-SCN) based on the classical SCN is proposed to improve the algebraic properties of output weighted least squares analytical solutions and avoid the structural risk of the model overfitting. For the ball mill load operation status recognition under a wide range of non-stationary operating conditions, L2-SCN method was used to identify the ball mill load operating conditions. The experiment results on the ball mill show that the proposed L2-SCN model has relative advantages in terms of accuracy and stability compared with the classic SCN model and the random vector functional link network (RVFL).
    Application of Adaptive Generalized Predictive Control Based on PSO in Microturbines
    MA Cao-yuan, ZHU Xin-shang, HAN Yong-gang, GAO Ai-jie
    2019, 26(2):  179-184. 
    Asbtract ( )  
    Related Articles | Metrics
    According to the characteristics of large time delay, nonlinearity and time-varying in micro gas turbines, based on the theory of system identification and adaptive generalized predictive control algorithm, a new method of micro turbine speed control is presented. Frist, through the acquisition of the micro gas turbine rotor system input (fuel) - output (rotor speed) data, the CARIMA model of the micro gas turbine rotor speed system is identified by using the FFRLS algorithm. Then, an adaptive generalized predictive controller of PSO is designed based on the identified CARIMA model. Finally, simulations are carried out in MATLAB. Simulation results show that, when the load is abrupt, the fuel quantity is fast, the speed of the rotating speed is small, the tracking effect is perfect, the robustness is strong, and the control performance is also good.
    A Novel Haze Removal Algorithm for Atmospheric Degraded Image with Dark Channel Prior
    XIE Li, XIONG Gang, YU Bo, ZHU Feng-hua, HU Bin
    2020, 27(02):  207-211. 
    Asbtract ( )  
    Related Articles | Metrics
    In the fog, haze and other severe atmospheric conditions, the image will be severely degraded, the practical value of the image will be affected greatly. In this paper, the removal of haze for the degraded image is studied. Firstly, the basic principle of fog imaging is analyzed. Then, through the analysis of the dark channel prior principle, a novel dark channel prior haze removal algorithm with the peak signal-to-noise ratio is proposed to improve the dehazing image details clear degree effectively. Finally, the simulation results are compared with histogram equalization, Multi-scale Retinex and other classical dark channel prior algorithms to verify the effectiveness of the proposed algorithm.

    Multi-car Elevator Systems Using Dynamic Zoning Based on Fast R-CNN

    LIU Jian, ZHAO Yue, XU Meng, CHANG Ling
    2019, 26(1):  208-0214. 
    Asbtract ( )  
    Related Articles | Metrics
     In order to improve the efficiency of the vertical transportation system effectively in limited space, multiple elevator cars are installed in a single elevator shaft, which is called "one shaft, multi-cars" elevator or multi-car elevator, which is the best choice to raise the transportation efficiency and solve the congestion in the vertical traffic. For the multi-car elevator scheduling, this paper puts forward a multi-car elevator scheduling method using dynamic zoning based on fast region-based convolutional network (Fast R-CNN). Firstly, fast R-CNN model is used to detect the number of people in the front of the hall and in the car; Then, elevators are reasonably dispatched according to the detection results; Finally, a zone is allocated to a car according to the assignment of calling to the car. The experimental results show that the proposed method is applicable to all kinds of elevator traffic patterns, and has higher operation efficiency and flexibility.
    Event-triggered Consensus Control for Platooning of Vehicles
    YANG Jian-ping, HU Jiang-ping, LV Wei
    2019, 26(3):  393-397. 
    Asbtract ( )  
    Related Articles | Metrics
    We consider the platooning problem for a group of autonomous mobile vehicles. In order to reduce the energy consumption of communications among vehicles in the moving process, we present an event-triggered consensus control approach. The safe distance is added to avoid collision between the adjacent vehicles. We firstly design event-triggered controllers for all the vehicles in the platoon. Besides, an event-triggering mechanism is analyzed and we prove that the Zeno behavior is avoided in the event-triggered process. Finally, numerical simulations are provided to verify the effectiveness of the proposed approach.
     Based on Particle Swarm Algorithm and Differential Evolution Flower Pollination Algorithm for Reactive Power Optimization
    MA Li-xin, WANG Li-ya , DONG Ang
    2019, 26(4):  613-618. 
    Asbtract ( )  
    Related Articles | Metrics
    Reactive power optimization of the power system is an effective way to keep the power system safe and economical. The main purpose of reactive power optimization is that it can improve the voltage quality and reduce the active power loss of the power system. The reactive power optimization problem of the power system is a complex and nonlinear problem and it should adjust the variables including control variables and state variables. This paper establishes a differential evolution flower pollination algorithm based on particle swarm optimization (DFPA-PSO) in view of the shortcomings of the accuracy of the traditional particle swarm optimization algorithm. The DFPA-PSO combines global search, local search and mutation operations with the flower pollination algorithm. Not only can it widen the search space of particles, but also it increases the diversity of the particles. The DFPA-PSO is applied to the IEEE-14 bus system, which takes into account of loss minimization, voltage level best target and maximum static voltage stability margin. Compared with other algorithms, the results show that DFPA-PSO has stronger global searching ability, faster convergence rate, better robustness and the active power loss is also reduced, thus proving the superiority of DFPA-PSO.
    Wind-light Generation System Optimization Based on Knowledge Fusion PSO Algorithm#br#
    #br#
    HU Ying, ZANG Da-jin, ZHANG Yong, LU Yuan
    2019, 26(5):  799-805. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the reliability of wind-light generation system and reduce the operation cost, a configured optimization method of wind-light generation system based on knowledge fusion particle swarm optimization (PSO) algorithm is presented, in which the optimization target is minimizing system installing cost and the constraint condition is power supply reliability. Firstly, in allusion to the limitation of local convergence of particle swarm optimization, using chaotic local PSO algorithm to improve its convergence; Then, clustering particle swarm using a simple method if the particle did not jump out of local optimum, and searching the global optimal particle meticulously according to the position of cluster center that optimizing the population which composed of the objective function value. Finally, the experimental results on 5 Benchmark test functions and optimizing configuration of wind-light generation system show that the effectiveness and applicability of the proposed method.
    A Convex Hull Vertices-Based Fault Diagnosis Algorithm for EMU Braking System
    GUO Tian-xu, TAI Xiu-hua, CHEN Mao-yin, ZHOU Dong-hua
    2019, 26(6):  1011-1014. 
    Asbtract ( )  
    Related Articles | Metrics
    The brake system is one of the crucial systems to ensure the safe and normal operation of EMU. The fault diagnosis problem of EMU braking system is studied in this paper. Various types of faults are reproduced based on the braking test platform of high-speed train in CRRC Qingdao Sifang Rolling Stock Research Institute Co., Ltd., China. Researches on fault detection and classification are carried out simultaneously. The convex hull selecting algorithm for fault diagnosis is proposed, which overcomes the problem that the classical convex hull solving algorithm cannot select convex hull vertices in higher dimension due to the high complexity. Based on the proposed algorithm, a convex-hull-vertices-based fault diagnosis method is proposed as well. The proposed method is applied to the fault detection and classification of EMU braking system, and its effect is verified by experiments.

    Blade Tip Clearance and Blade Tip Timing Measurement Based on Microwave Sensors

    ZHANG Ji-long, DUAN Fa-jie, NIU Guang-yue
    2019, 26(7):  1233-1238. 
    Asbtract ( )  
    Related Articles | Metrics
    Blade tip clearance and blade vibration are important parameters which affect the efficiency, operation safety and life span of turbomachinery. To meet the requirements of blade tip clearance and tip timing measurement under harsh working environments such as aircraft engine, a tip parameter measurement system based on microwave method is proposed, and the system can achieve the measurement of tip clearance and tip timing simultaneously. The system structure and measuring principle is analyzed. Microwave sensors of 24GHz based on microstrip antenna and PIFA are designed, the diameter of the sensor is less than 8mm. The sensors and measurement system prototype are tested in experiment and compared with the fiber optic tip timing system, the result indicates that the microwave measurement system can realize the dynamic measurement of blade tip clearance and tip timing, the measurement accuracy of tip clearance is ±35μm.
    Research on H∞ Control of Uncertain Hamiltonian Systems
    LAN Yong-hong, YIN Li-sha
    2019, 26(8):  1484-1489. 
    Asbtract ( )  
    Related Articles | Metrics
    By using Lyapunov stability theory, an observer-based H∞ adaptive controller design method was proposed for a class of Hamiltonian systems with parametric uncertainties in this paper. First, the H∞ controller design problem was investigated for nominal Hamiltonian systems and the obtained result was extended to Hamiltonian systems with parametric uncertainties. The H∞ adaptive controller was also proposed. Next, considering the immeasurable of the system states and according to the structural characteristics of uncertain Hamilton systems, an observer-based H∞ adaptive controller design method was presented. Finally, the validity of the proposed method is verified by a numerical example.
    Research on Stage Wire Smooth Transmission Method with Zero Speed Parking 
    LI Wei, GE Zhen-fu, GONG Jian-xing
    2019, 26(9):  1605-1612. 
    Asbtract ( )  
    Related Articles | Metrics
    In terms of problems of 2D stage wire system designing that the poor performance of synchronous coordination, bad attitude curve and difficulties of ADRC parameter tuning caused by traditional staged control and inertia brake, a synchronous coordinating control method with zero speed parking mode of stage wire system is proposed, which is on the basis of ADRC technology and starting from establishing the disturbance rejection mode. First of all, it uses LESO and bandwidth-parameterization to simplify the parameter tuning of ADRC, then ensure the control performance of single wire system; Then, the suitable smooth transmission and deceleration algorithm is designed to achieve its smooth parking and zero speed braking as well as improve the track fitting effect. The simulation results show that, compared with the traditional control system, the control scheme presented in this paper shows better synchronous coordination performance and track fitting effect, it is also an effective way to ensure the stage wire dancing with the music.
    Design of Control System for Landing Pose Simulation Mechanism 
    XIE Zhi-jiang, ZHOU Yang, GUO Zong-huan
    2019, 26(10):  1789-1795. 
    Asbtract ( )  
    Related Articles | Metrics
    According to the requirements of lunar sampling experiment, a motion control system based on PC control technology and high speed Ethernet bus EtherCAT technology is designed to realize the lifting, pitching and rolling high-precision position adjustment functions of the lunar landing pose simulation mechanism. The closed-loop and synchronization control strategy of the mechanism are analyzed. The inverse solution of the mechanism is deduced. The hardware structure of the control system is established. The TwinCAT software is used to develop motion control program of the mechanism. The pose adjustment function of the mechanism is realized through the combination of hardware and software. The results show that the control system can realize the continuity and synchronization of the motion of the pose adjustment mechanism, and meet the requirements of the high precision index of the sampling equipment.
    Research on Reliability of Collision Sensor Based on Acoustic Wave Testing
    JIA Wei-bin, YAN Chen, JI Xiao-yu, XU Wen-yuan
    2019, 26(11):  1971-1977. 
    Asbtract ( )  
    Related Articles | Metrics
    The reliability of the collision sensor under acoustic wave excitation is tested and analyzed. The MEMS (Micro Electro Mechanical Systems) structures and their working principles are analyzed and explored. Through the self-built system, the acceleration value measured by the collision sensors is analyzed, and the simultaneous test frequency value is read, then they are combined for data analysis. On this basis, acoustic wave from multi-device, multi-frequency point, multi-direction and different modulation methods are used to evaluate the reliability of the collision sensor, which can avoid the situation that the air bag explode in the error cases.

    Multi Core SVM Fault Diagnosis of Diesel Engine Based on Dimension Measurement

    LIU Xiang-bo, YANG Li-he, SUN Yu-de
    2019, 26(12):  2211-2217. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the performance of diesel engine fault diagnosis, a method of multi core SVM fault diagnosis for diesel engine based on dimension measurement is proposed. Firstly, the internal combustion engine dimension measurement is defined, and the dimension measurement system and process design are carried out; Secondly, the multiple kernel SVM characteristics, the input fault features from the original data space is mapped to a high dimensional data space, and the use of Lagrange method to achieve primal dual solution, and then follow the principle of Mercer realize diesel multiple kernel SVM fault diagnosis; Finally, the number of kernel functions and the recognition rate of different kernel functions are given, and the advantages of the proposed method are verified by comparing the calculation time and accuracy.

    Design and Simulation of Fractional Order Controller for Linear Inverted Pendulum

    2020, 27(1):  8-14. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to solve the problem of stability control of the linear inverted pendulum, the fractional order proportional integral (FOPI and FO[PI]) controller is designed to correct the system. Firstly, the mathematical model of inverted pendulum is established according to the Newton mechanics method. Then, using the gain robustness fractional order controller parameter simplified algorithm based on the vector designed the fractional order proportional integral controller. Finally, the validity of the fractional order proportional integral controller parameter tuning method is verified and fractional order proportional integral controller and integer order PID (IOPID) controller are used to carry out stability control simulation experiment and then compared and analyzed the angle response curves of the pendulum .The results show that the fractional order proportional integral controller has better stability control effect than the IOPID controller for the inverted pendulum systems, and in the fractional order proportional integral controller, the FO[PI] controller has better stability control effect for the inverted pendulum systems, with robustness, faster response time and less oscillation amplitude.

    Design of the Double Fuzzy Controller System for AA0 Sewage Treatment

    HUANG Chao, BO Cui-mei, GUO Wei, TENG Gang
    2019, 26(2):  185-190. 
    Asbtract ( )  
    Related Articles | Metrics
     According to the special requirement of aeration rate control in the aerobic pool based on the AAO sewage treatment technology, the intelligent control system is designed using the double fuzzy control algorithm. Through analyzing the principle of the control on the aeration rate of AAO technology, the double fuzzy controller is constructed based on the setting of fuzzy rule base, parameters are changed to advance the performance. Finally, this article describes the principle and the methods to accomplish the program of the double fuzzy controller by the use of programmable logic controller. This control method has been applied to the modern sewage disposal process, meeting the requirements of process and control.
    Structural Damage Reduced-order Model and Coupled Fault Isolation for Traction Motor
    ZHANG Kun-peng, JIANG Bin, CHEN Fu-yang
    2020, 27(02):  212-217. 
    Asbtract ( )  
    Related Articles | Metrics
    A novel coupled fault isolation scheme is proposed to deal with multiple, simultaneous and coupled nonlinear faults for traction motor with structural damage. The structural damage reduced-order model is firstly built by introducing the relative balance factor associated with big data driven classifier algorithm. The proposed discrete-time fault model has been established with the help of Delta operator and support vector machine (SVM). Meanwhile, fault isolation condition and threshold determination techniques are used to isolate the coupled faults. Finally, through a coupled fault isolation experiments using real data of fault-injection benchmark for traction drive control system, the effectiveness of the proposed algorithm is justified.
    Disturbance Compensation Based Backstepping Control for Trajectory Tracking of Mobile Robots
    SHEN Zhi-peng, ZHANG Xiao-ling
    2019, 26(3):  398-404. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to eliminate the velocity jump in the wheeled mobile robot trajectory tracking under external disturbances, a fuzzy adaptive backstepping control method with disturbance compensation is proposed. The disturbances caused by the system model uncertainty and external disturbances are estimated by a fuzzy system and the effect of disturbance estimation error on the controlled system is restrained by introducing the sliding-mode control. The corresponding control law and parameter adaptive law for the fuzzy system are given through the backstepping method. The stability analysis has proved that the closed-loop system is globally uniformly asymptotically stable. The simulation results show that the controlled system under external disturbances can achieve a fast transient response, overcome the sliding mode chattering and eliminate the velocity jump.
    Research on Short-Term Load Forecasting Method Based on Multi-Model Fusion Neural Network
    XU Yan-lu, ZHANG Jian-sen, JI Xing, WANG Bin-bin, DENG Zhuo-fu
    2019, 26(4):  619-624. 
    Asbtract ( )  
    Related Articles | Metrics
    Power industry requires accurate short-term load forecasting to provide precise load requirements for power system control and scheduling. In order to improve the accuracy of short-term power load forecasting, a method based on FFT optimized ResNet model is proposed. The model first defines power load forecasting as a time series problem, then introduces one-dimensional ResNet for power load regression prediction, and uses FFT to optimize ResNet. The FFT transform of a layer of convolution results gives the model the ability to extract periodic features in the data. Experiments show that the prediction accuracy of FFT-ResNet is better than several benchmark models in 6-hour power load forecasting, which indicates that this method has a good application prospect in power load forecasting.
    Neural NARX Model for Hysteresis in Piezoelectric Actuators
    ZHANG Xin-liang, JIA Li-jie, FU Chen-lin
    2019, 26(5):  806-811. 
    Asbtract ( )  
    Related Articles | Metrics
    To describe the rate-dependent hysteresis behavior of the piezoelectric actuators, a cascade block-based model is proposed in this paper, i.e., a rate-independent hysteresis block cascading with a rate-dependent block. For the approximation of the hysteresis block, a hysteresis operator is introduced into the input space to represent the changing tendency of the gradient with the hysteresis. Then a neural hysteresis sub-model is constructed based on a one-to-one mapping. Meanwhile, to describe the rate-dependent characteristics of the dynamic hysteresis, a NARX (nonlinear autoregressive model with exogenous inputs) model is adopted. And a recursive stochastic Newton approximation algorithm is derived for the optimization of the model. The validation results have shown the effectiveness of the proposed model for characterizing the dynamic hysteresis.
    Crowd Counting Algorithm Based on Local Density Classification
    FAN Long-fei, JIANG Zi-zheng, LI Hai-feng, CHEN Xin-wei
    2019, 26(6):  1015-1020. 
    Asbtract ( )  
    Related Articles | Metrics
    Since the accuracy of the crowd counting is influenced by crowd density, a novel method for crowd counting is presented. Firstly, in the pre-processing stage, a sub-crowd segmentation method based on sliding window is designed, which improves the efficiency and precision. Secondly, the sub-crowds are divided into high-density and low-density. Then these two sub-crowds separately are trained off-line and choose the best feature combination and the regression model by experimental method. Finally, the selected combination of features and regression model are utilized to predict the number of persons. Compared with the state of the art algorithms, the average estimation error of the proposed algorithm is 18.9 % smaller, which proves the effectiveness of the algorithm.
    Sparse Fault Degradation Oriented Fisher Discriminant Analysis Based Fault Trace
    FAN Hai-dong, WANG Yue, LI Qing-yi, ZHAO Chun-hui
    2019, 26(7):  1239-1244. 
    Asbtract ( )  
    Related Articles | Metrics
    The thermal power processes contain many variables, while only a part of variables will be influenced when the fault occurs. It is meaningful to analyze the fault causalities, which may help track root fault reasons and locate abnormal components. Therefore, for the fault processes, this paper isolates the faulty variables on basis of sparse fault degradation oriented fisher discriminant analysis (FDFDA) and then analyzes the causalities between different variables by Granger Causality analysis for identifying root faulty reasons.
    A Random-finite-set Approach to SLAM Based on Amplitude Information
    SHI Jian-ming, ZHANG Fei, ZENG Qing-jun, SUN Tao-ying
    2019, 26(8):  1472-1478. 
    Asbtract ( )  
    Related Articles | Metrics
    Taking account of the problem that the simultaneous localization and mapping (Simultaneous Localization and Mapping, SLAM) method of underwater vehicle has low accuracy in the underwater environment with dense clutter and many map feature points, an improved random-finite-set to SLAM based on amplitude information has been proposed in this paper. The method uses the amplitude information of map features to estimate the map feature set and to obtain more accurate map features and clutter likelihood function, which improve the estimation accuracy of the feature map in SLAM process. This paper has researched the performance of the PHD-SLAM method with the addition of the amplitude information in the case of the known signal to noise ratio and the unknown signal to noise ratio. The results show that the proposed algorithm outperforms RB-PHD-SLAM in estimation of the number and location of map features and calculation efficiency.

    Background Modeling Based Payload Swing Angle Measuring Method of Bridge Crane System

    XU Peng, FANG Yong-chun, CHEN He
    2019, 26(9):  1613-1619. 
    Asbtract ( )  
    Related Articles | Metrics
    Traditional angle measuring devices of bridge crane are installed in the crane system, usually using contact measuring device with potentiometer or photoelectric encoder, which have the disadvantages of complicated mechanical structure, poor independence and so on. Utilizing visual techniques, this paper proposes a computer vision based method to achieve the non-contact angle detection objective. Meanwhile, in order to improve the accuracy of payload identification and realize real-time operation, it uses the background modeling method with background subtraction for rapid recognition of moving payload to calculate the payload angle. Through experimental verification, it can be seen that this method recognizes moving payload sufficiently fast in real time, and calculate the load swing angle accurately. In particular, the algorithm does not depend on the geometry and quality distribution of the payload, which can be used to achieve accurate angle measurement for all types of payloads, making it suitable for industrial crane systems. 
    A Method Based on Multi–sensor Data Fusion in Gimbal Self-stabilization Control 
    LI Hui-jun, YUAN Shuai, TANG Xiang, TANG Chao-quan
    2019, 26(10):  1796-1802. 
    Asbtract ( )  
    Related Articles | Metrics
    The stability of gimbal has great influence on carrying equipment’s accuracy. In order to make gimbal keep balance, a self-stabilization control method of gimbal based on multi-sensor data fusion is proposed. AHRS(Attitude and heading reference system) based on three-axis gyroscope, accelerometer and geomagnetic is adopted to obtain angular velocity, acceleration and geomagnetic intensity. Kalman filter algorithm is used to filter the acceleration and quaternion is adopted to fuse three kinds of information to get gimbal’s pitch and yaw angle. The control method is cascade double closed-loop PID. Experimental results show that this method make the gimbal remain stable in a complex environment with high accuracy and anti-jamming capability at the same time the overshot is small and robustness is strong.
    Intermittent Fault Diagnosis and Fault Tolerant Control Based on Two-layer Kalman Filter
    SHEN Shi-kun, QIU Ai-bing , QIU Wei-dong, CHEN Juan
    2019, 26(11):  1978-1985. 
    Asbtract ( )  
    Related Articles | Metrics
    In this paper, a design framework of intermittent fault (IF) diagnosis and fault tolerant control (FTC) is developed for a class of linear discrete-time systems disturbed by noise. Firstly, a two-layer Kalman filter scheme is employed to realize IF isolation and estimation accurately. The first layer Kalman filter can detect and isolate the actuator intermittent fault by constructing the weighted square sum of the filter error as the system residual. The second optimal Kalman filter achieves a joint optimal estimation of system state, fault-free constraint state and intermittent fault by reconstructing the filter gain into a fault-free constrained gain and an intermittent fault gain, and solving the problem of the minimum variance unbiased estimation under the intermittent fault gain constraint. Furthermore, the optimal estimation, linear quadratic Gaussian (LQG) control and fault decoupling are used to construct the active fault-tolerant controller, so that the system can still guarantee the system performance in case of intermittent fault. Finally, the effectiveness of the proposed method is verified by the simulation of DC motor control system.

    Modified Teaching-learning-based Optimization Algorithm for No-wait Flow-shop Green Scheduling Problem

    DU Ao-Ran, QIAN Bin, HU Rong, ZHANG Chang-Sheng, WANG Ling
    2019, 26(12):  2218-2224. 
    Asbtract ( )  
    Related Articles | Metrics

    In this paper, a modified teaching-learning-based optimization algorithm, namely MTLBO, is proposed to minimize the energic power cost criterion of the no-wait flow-shop green scheduling problem with sequence-dependent setup times and release dates, which considers a serial of environmental impacts and the rising energy costs in recent years. Firstly, a speed-up evaluation method is developed according to the property of the algorithm. Secondly, in the teacher phase, the overall quality of the population can be improved by Insert operation for the learner with the worst grades or the problem solution. Meanwhile, a self-adapting teaching factor is put forward to improve the global search ability of MTLBO. Thirdly, the insert-neighborhood local search is proposed to strengthen the local search capability, which contributes to achieving a reasonable balance between global and local search of the algorithm. Simulation results and comparisons show that MTLBO is more robust and efficient than the other optimization methods.

    Application of BDD Algorithm in Overhead Contact Line System Failure Risk Assessment

    ZHAO Feng, CHEN Xian, WANG Ying
    2020, 27(1):  15-21. 
    Asbtract ( )  
    Related Articles | Metrics
    The possibility and the severity of the consequences for the failure of OCS(Overhead Contact Line System) is considered and analyzed accurately, and the failure risk is assessed in time to provide a theoretical basis for the development of risk control measures. Firstly, the failure fault tree of OCS is established, and then the BDD structure is generated by the ITE rules. The top event risk, the Birnbaum importance and the critical importance of the basic events are calculated by recursively accessing the nodes of the BDD structure from top to bottom. According to the BDD algorithm, the C# program is finished, thus the occurrence probability of failure accident for OCS and the key factors causing the accident can be obtained. Compared with the cut set method, the BDD method can not only get the exact values of the occurrence probability of top event and the importance of basic events, but also have the advantages of fast calculation speed and simple procedure.

    Voltage Stability Strategy of Self-excited Induction Generator Based on Predictive Current Control

    SUN Jing, YANG Da-liang, GONG Ping-ping, LI Zhuo
    2019, 26(2):  191-195. 
    Asbtract ( )  
    Related Articles | Metrics
    To deal with the voltage sag problem of the stand-alone self-excited induction generator (SEIG) when loading, a voltage regulation system based on the static synchronous compensator (STATCOM) is designed to maintain a constant terminal voltage of SEIG under loading conditions. In order to improve the transient performance and adaptation ability of the voltage regulation system, a predictive current control (PCC) method is proposed to design inner loop current controllers so that the transient performance and adaptation ability of the voltage regulation system will ultimately improve. Simulation results show that the proposed approach can improve the loading capacity and current tracking capabilities of SEIG very well compared with the classical methods. Terminal voltage performs well in robustness and regulation when loading. It has been shown that the proposed control method works very effectively.
    Image Based Semimolten Condition Diagnosis System of Fused Magnesium Furnace
    GUO Zhang, WANG Ke-dong, CHENG Meng-meng, LIU Xiao-li, LU Shao-wen
    2020, 27(02):  219-225. 
    Asbtract ( )  
    Related Articles | Metrics
    电熔镁炉生产过程中，“欠烧”是一种异常工况，需要及时发现和处理。目前，欠烧工况主要依靠有经验的巡检工人在生产现场“看火”。工人劳动强度大，且容易漏检、误检。本文提出了一种基于视频监控图像的欠烧工况自动判别技术。采用多元图像分析技术提取炉口火焰的可视化特征，采用AdaBoost（决策树）建立欠烧工况的分类器模型，设计开发了欠烧工况的视频监控系统，并将该系统在某电熔镁炉厂的实际生产中进行了实验。结果表明，该欠烧工况图像判别系统能够准确、及时地判断出欠烧工况，而且避免误报、漏报的现象。
    Output Feedback Gain-scheduled Switching Control for Hypersonic Vehicles
    HUANG Yi-qing, JIANG Yan, LI Zhi-kun, GE Yuan
    2019, 26(3):  405-411. 
    Asbtract ( )  
    Related Articles | Metrics
    This article aims to develop output feedback gain-scheduled scheduled switching tracking control techniques for a hypersonic vehicle based on the linear parameter varying (LPV) observer. Firstly, an LPV state observer is designed to estimate the unmeasured vehicle state variables, then, applying the estimated system state, a sub-region output feedback gain-scheduled controller is designed for each parameter sub-region. Secondly, according to the developed sub-region output feedback gain-scheduled controllers and the switching function which is defined by the value of scheduling parameters, a gain-scheduled switching controller is obtained, which guarantees the closed-loop system to be asymptotically stable and satisfies the given tracking error performance index. The observer error and tracking error are proved to converge to a small neighborhood of the origin via the multiple Lyapunov functions (MLFs) analysis method. Finally, simulation results show that the proposed controller performs well and exhibits good tracking performance.
    The Temperature Control System of Vacuum Annealing Furnace Based on Fuzzy Control
    LUO Dong-song, SUN Guan-qiong
    2019, 26(4):  625-630. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at the problems such as slow response, large overshoot quantity, poor anti-jamming ability and hysteresis in the temperature control process of vacuum annealing furnace, this paper puts forward a self-tuning fuzzy PID control strategy and designs a self-tuning fuzzy PID controller to achieve parameter detection of the vacuum annealing process and optimization control of the whole process. This article takes the production equipment and main technical parameters as a starting point, designs an industrial annealing furnace temperature control system which is based on PLC, intelligent instruments and fuzzy PID self-tuning technology. The simulation of the self-tuning fuzzy PID control algorithm is realized by MATLAB and the results are observed, finally the on-optimization of system parameters is realized. The actual operation shows that the system is reliable, the parameters are able to meet the requirements.
    Fuzzy Compensation Control System for Lower Limbs Rehabilitation Robot
    CHEN Yu, XIA Tian, ZHANG Li, HUAN Xi
    2019, 26(5):  812-817. 
    Asbtract ( )  
    Related Articles | Metrics
    To study the control system of the lower limbs rehabilitative robot, through the modeling of lower limbs rehabilitative robot and kinematics analysis, a fuzzy compensation control algorithm is proposed for the friction interference generated during the motion. Firstly, analyze the motion model and establish the dynamic equation. Then, for the friction generated during the movement of interference, a fuzzy compensation friction interference control method based on the traditional fuzzy compensation control method is proposed. The motion trajectory of the lower limb rehabilitation robot is realized by interpolating the output trajectory through the Googol motion controller. According to the simulation experiments, this control method can be a good compensation for the impact of friction interference factors.
    Multi-image Synchronous Encryption Algorithm Based on Hyper-complex Fusion Model 
    TIAN Wen, LI Su-ruo, HU Yu-rong
    2019, 26(6):  1021-1028. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to solve the defects as low security and decryption image distortion in current multi-image encryption technology, a new multi-image synchronous lossless encryption algorithm based on hyper-complex fusion model and fractional order chaotic dynamics permutation is proposed. The fractional order logistic map was constructed, and the dynamical permutation mechanism was designed by considering the pixels of each plain to permute all the plains. And four DCT coefficient matrixes were got based on discrete cosine transformation. Then the hyper-complex fusion model was designed to lossless fuse the four coefficient matrixes for obtaining composite matrix. Then the complex scrambling image was got by inverse DCT transform. Finally, chaotic mask was got by iterating the fractional order chaotic map again, and pixel encryption mechanism was designed by jointing the FrFT transform to realize the Multi-image encryption. The experimental data show that this algorithm has higher security and restoration quality. 
    Multi-variable Fault Detection Method Based on Reconstruction Contribution Analysis
    ZHANG Ze-yu, LV Feng, DU Wen-xia, ZHAI kun, HUANG Zhan-ping
    2019, 26(7):  1245-1249. 
    Asbtract ( )  
    Related Articles | Metrics
    A multi-variable fault detection method based on reconstruction contribution analysis is proposed in view of the characteristics of multiple variables, large amount of collected data and varied data during the operation of complex systems. The improved reconstruction method can eliminate the shortcomings of the traditional SPE contribution graph method, such as insensitivity to fault data and insufficient diagnostic ability, and can conduct fault location when multi-variable faults occur simultaneously after the establishment of PCA model. The experimental simulation of the wind turbine system shows that this method can achieve accurate diagnosis when the faults of multiple variables occur simultaneously, no matter whether there are minor faults with gradual changes or abrupt changes.
    The Database Selection Based on Hesitant Linguistic Information Aggregation Algorithm
    GAO Ting, WANG Xiao-nan
    2019, 26(8):  1444-1449. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the efficiency of database selection, and solve problem of the multi-attribute group decision making (MAGDM). It puts forward a method of the database selection based on hesitant linguistic information aggregation. Firstly, a database selection model on the basis of the generalized hesitant linguistic Heronian mean (GHLHM) operator is developed. Secondly, under the hesitant linguistic environment, the new operations are defined based on the Archimedean norms. Then, by using the defined operational laws and Heronian mean, the GHLHM operator is proposed, whose desirable properties and some special cases are discussed in detail. The generalized hesitant linguistic weighted Heronian mean (GHLWHM) operator is introduced. In addition, a novel hesitant fuzzy linguistic MAGDM model based on GHLWHM operator is investigated, which can capture the relationship among the input decision making information and enable decision maker to select different parameters to make decision. Finally, the practicality and effectiveness of the developed model is illustrated with a numerical example for the selection of database. Experiments show that this method can achieve comprehensive optimization of database performance, and has broad application prospects in other fields.
    Fast Power-balancing Control for Dual PWM Converters
    ZHONG Li-qun, WANG Hui, WU Xuan, XU Xue-gang
    2019, 26(9):  1620-1626. 
    Asbtract ( )  
    Related Articles | Metrics
    A dc-link power-balancing control method is applied to a dual PWM converters system. Based on the converter and inverter power differential equations derived by their mathematical model, the strategy is to fully utilize the inverter dynamics in controlling the converter dynamics so that the converter power matches the required inverter power exactly and thus the dc-link capacitor power can keep invariant. To simplify the calculation of the load power differential, the IP control method is used in the permanent magnet synchronous motor. At the same time, in order to keep the dc-link voltage more stable, the outer loop of the converter is the dc-link voltage control. So the dc-link voltage remains stable even a very small amount of the dc-link capacitance is used. Simulation and experimental results verify the effectiveness and superiority of the proposed method. 
    Research on the Walking Model of Lower-Limb Walking Assist Exoskeleton
    HE Yu-yi, Li Pei-xing, YAN Wei-xin, ZHAO Yan-zheng
    2019, 26(10):  1803-1809. 
    Asbtract ( )  
    Related Articles | Metrics
    The widely used method of gait planning for the lower-limb walking assist exoskeleton, based on the captured walking trajectories from the able-bodied people, has many disadvantages. A gait modeling method based on the kinematics and dynamics of the lower-limb walking assist exoskeleton is put forward. The motion curves of various time-varying parameters in the model for gait analysis are obtained, which provides theoretical basis for the autonomous gait planning when the walking parameters vary. The problem of parameter adaptability of the trajectory planning can be solved. The experimental results show that, this method aimed at satisfying the specific requirements of the lower-limb walking assist exoskeleton, can obtain the optimized parameters of different configurations, and plan the optimized walking motion of the exoskeleton.
    Fault Detection Method Based on Weighted k Nearest Neighbor in Multimode Process
    FENG Li-wei, ZHANG Cheng, LI Yuan, XIE Yan-hong
    2019, 26(11):  1986-1993. 
    Asbtract ( )  
    Related Articles | Metrics
     Industrial processes often operate in multiple production modes, for the characteristics of larger variables, the center drift and the larger modal variance of the multi-modal data, a weighed k-nearest-neighbor fault detection method(FD-wkNN) is proposed. First, find the k nearest neighbor in the training data set and calculate the distance between the training sample and the k nearest neighbor, and calculate the average distance of between the k nearest neighbor and the first K local nearest neighbors, take the reciprocal of the average distance as the distance weight, take the weighted distance as statistic D, D is able to eliminate the influence of center drift and difference of modal variances. Second determine the control line using D distribution. Finally compare the calculation D statistics of online sample and control line. On-line fault detection is realized. Using multi-mode example, as well as examples of penicillin data simulation experiments, compared with the PCA, kPCA, FD-kNN method to verify the effectiveness of this method.

    Improved EDA Solving Green Reentrant Job Shop Scheduling Problem

    XIE Zheng-Ming, QIAN Bin, HU Rong, XIANG Feng-Hong, WANG Ling
    2019, 26(12):  2225-2230. 
    Asbtract ( )  
    Related Articles | Metrics
    In view of the huge impact to the environment in the production process, a HBEDA for solving the MRJSGSP_DD is put forward to achieve minimization of MT and TEC. Firstly, in the initialization phase of the algorithm, a group of random population is generated to guarantee the randomness and diversity of the population, and the non-dominated set is constructed. Then, HBEDA is introduced to construct the probabilistic model. The model can learn the relation between the orders of jobs and enhance the global searching ability of the algorithm. Finally, by using the characteristics of the problem, an enhanced local search method is designed. The effectiveness of the algorithm is verified by simulation and comparison.
    Modeling and Detection of Stator Inter-turn Short Circuit Fault in Induction Motor#br#
    #br#
    SHI Yong-qian, JIANG Bin, MAO Ze-hui
    2020, 27(1):  22-27. 
    Asbtract ( )  
    Related Articles | Metrics
    The stator inter-turn short circuit fault of asynchronous motor is one of the typical stator faults. To ensure the safe operation of the motor, it needs to detect the fault in time and take measures immediately. Mechanism modeling of asynchronous motor with stator inter-turn short circuit fault is built in the two-phase synchronous rotating coordinate system, which is transformed into the form of state equation. Based on the asynchronous motor of CRH2, simulation research is carried. It detects the fault by multiple model matching with inter-turn short circuit coefficient. The simulation results verify the accuracy and effectiveness of the model, and the fault of asynchronous motor is detected by multiple model matching.

    Control of Revolving Inverted Pendulum Based on PSO-FOPID Controller

    WEI Li-xin, WANG Hao, MU Xiao-wei
    2019, 26(2):  196-201. 
    Asbtract ( )  
    Related Articles | Metrics
    The rotary inverted pendulum is a strong coupling, nonlinear and unstable system which has one input and two outputs. In order to realize the effective control of the system in the stable stage, fractional order PID, PIγDμ, and FOPID are used in the pendulum angle and rotation angle's position and speed closed-loop control, respectively. Because of the large number of FOPID controllers and parameters, manual setting of the controller parameters is very complicated and not easy to achieve. Therefore, this paper uses the improved multi-objective particle swarm algorithm (IMOPSO) to adjust FOPID controller parameters. The effectiveness of the IMOPSO-FOPID algorithm is verified by the QUBE-Servo the rotary inverted pendulum. The inverted pendulum obtains good dynamic quality and stability, better than PID.
    Research on a Method for Forecasting the Short Life Cycle Experiential Product during Preparation Period
    TANG Zhong-jun, DONG Shun-Peng
    2020, 27(02):  226-233. 
    Asbtract ( )  
    Related Articles | Metrics
    It is difficult to effectively forecast overall sales volume of short life cycle experiential products using traditional methods with data point forecasts during the preparation period, because of fuzzification of variables and a lack of historical sales data. To address this problem, a method for forecasting interval reliability classification of short life cycle experiential product during preparation period is proposed based on rough set and evidence theory. This method use rough set theory to get reliability function from each variables and use evidence theory to set up comprehensive reliability. The comprehensive reliability value of the training set is used to construct the classification reliability interval, so as to judge the classification reliability interval from the comprehensive reliability value of the test set , and obtain the classification reliability interval of the test set finally. 621 samples selected from domestic films released during 2016-2018 are used to verify the effectiveness of the proposed method, and the intersectional verification results shows the forecasting method has great accuracy.

    Design of a Rapid Arctangent-based Tracking Differentiator

    REN Yan, ZHAO Guan-hua, LIU Hui
    2019, 26(3):  412-416. 
    Asbtract ( )  
    Related Articles | Metrics

    In order to solve the problem that the arctangent tracking differentiator has difficulty in setting parameters and slow convergence near the equilibrium, the author has designed a fast convergence arctangent tracking differentiator. A rapid arctangent tracking differentiator is constructed by introducing linear functions and terminal attractor functions into the arctangent function and its stability is proved, which makes the system far from the equilibrium and close to the equilibrium point convergence rapidly and stably to the equilibrium point. This continuous function form of linear and nonlinear combination enhances the tracking ability of the system, and effectively suppresses the noise, which can realize fast and precise signal differential and tracking, and the form is simple and easy to implement. The simulation results show that the rapid arctangent tracking differentiator has excellent performance.

    Probabilistic PLS Based on Re-extraction of Residuals and Its Application in Process Monitoring
    LI Qing-hua, PAN Feng, ZHAO Zhong-gai
    2019, 26(4):  631-637. 
    Asbtract ( )  
    Related Articles | Metrics
    The objective of the probabilistic partial least square (PPLS) algorithm is to maximize the correlation of scores of process variables and quality variables, and imposes no restriction on residuals, which will result in large information containing in the residuals. The paper proposes a PPLS algorithm based on re-extraction of residuals. After the development of the PPLS model, this algorithm performs further decomposition on residuals to obtain another set of scores and residuals. As a result, process variables and quality variables can be projected into the correlation score subspace, the score subspace for the quality-irrelevant process variables, the residual subspace for process variables, the score subspace for un-predicted quality variables, and the residual subspace for quality variables. To identify the parameters, the maximum-likelihood method along with the expectation-maximization (EM) algorithm is employed. Moreover, by constructing the monitoring statistics, this model is introduced into process monitoring, and its application in the numerical simulation case illustrates its validity.
    H∞ Control for a Class of Time Delay LPV Discrete Systems with Packet Dropouts
    MA Tao, JIANG Shun, PAN Feng
    2019, 26(5):  818-824. 
    Asbtract ( )  
    Related Articles | Metrics
    This paper focuses on the problem of H∞ control for linear parameter varying (LPV) discrete time systems with a parameter varying state delay and packet dropouts. The time-delay and state matrix of LPV discrete systems are deterministic functions with parameter variation, the parameter is measurable and constantly changing. Thus, we propose a new H∞ performance criterion depends on the time-varying parameters. The guidelines by introducing an additional matrix eliminates the coupling between Lyapunov functions and system matrices，and it is easier to achieve Value. Under the new condition，the H ∞ state feedback controllers are designed. By using the linear matrix inequality technique, sufficient conditions for the existence of the controller are obtained. Further transformation can obtain the existence condition of the solution of the inequality. Finally, the validity of the method is verified by numerical simulation.
    Fuzzy Control Design for Periodic Dynamic Trajectory of TORA System
    ZHENG Gong-bei, GAO Bing-tuan, LIU Chuan-de, XIE Ji-hua
    2019, 26(6):  1029-1034. 
    Asbtract ( )  
    Related Articles | Metrics
    Traditional research work on underactuated (Translational Oscillator with Rotational Actuator, TORA) system mainly focuses on stabilizing control of equilibrium points. In this article, a fuzzy control design scheme easy to realize is proposed to steer periodic oscillating trajectories of TORA system. Firstly, based on the dynamics of TORA, the frequency of translational oscillation platform is derived, and then the dynamic periodic orbits are followed, namely, the translational oscillation platform oscillating periodically while the rotational proof mass rotating with the fixed angular velocity. Secondly, based on the analysis of state variables, tracking error of system’s energy is employed as the inputs of fuzzy control system so as to reduce the dimension of the control system, membership function using one-side domain is applied to design fuzzy rules and the center of gravity method is used for defuzzification. Consequently, a practical fuzzy controller is achieved. Finally, simulation results and experimental results validate efficiency and practicability of the proposed control scheme.

    Bearing Fault Diagnosis Based on EEMD-Hilbert and Optimized Cyclic Spectrum

    WANG Xiao-hui, SUI Guang-zhou, GONG Man-feng
    2019, 26(7):  1250-1255. 
    Asbtract ( )  
    Related Articles | Metrics
    Against the weakening of mixed-fault signal characteristics because of severe operating conditions, a bearing fault diagnosis method based on EEMD-Hilbert signal reconstruction and improved cyclic spectrum correlation algorithm is proposed. First, the cyclic spectrum function at the modulation frequency of the system is derived from the traditional second-order cyclostationary theory, this function can eliminate interference by its appropriate mediation information. Second, the EEMD-Hilbert algorithm is designed, and then is applied to the cyclostationary signal to eliminate the interference from gaussian noise and colored noise. At the last, a simulation experiment of bearing fault diagnosis conditions is designed, and the experimental results show that this method can effectively enhance the characteristics of the weak cycled stationary signal and avoid missed sentences.
    Sliding Mode Based on Active Disturbance Rejection Control of Speed Governing System for PMSM
    HOU Li-min, REN Yi-fu, WANG Huai-zhen, LI Yun-zhuo, LI Xiu-jv
    2019, 26(8):  1460-1465. 
    Asbtract ( )  
    Related Articles | Metrics
    The traditional active disturbance rejection control (ADRC) system of permanent magnet synchronous motor (PMSM) has the problems of more adjustment parameters and complex setting. The sliding mode control method is used to improve the structure of ADRC, and sliding mode based on active disturbance rejection speed controller and the current controller are designed. The controller introduces sliding mode control in ADRC structure and improves extended state observer (ESO) and non-linear state error feedback (NLSEF) in ADRC. Based on retaining the original performance of ADRC, the controller simplifies parameter setting and improves the response speed and robustness of the system, and the stability was proved by using lyapunov theory. The simulation results show the effectiveness of the method.

    Robust Attitude Control of Hypersonic Vehicle Based on Active Disturbance Rejection Control

    PIAO Min-nan , SUN Ming-wei, HUANG Jian, CHEN Zeng-qiang
    2019, 26(9):  1627-1635. 
    Asbtract ( )  
    Related Articles | Metrics
    This paper proposes a unified scheme for the three-channel attitude control of the hypersonic vehicle based on the linear active disturbance rejection control (LADRC). For the control of Euler angles, three LADRC controllers are designed for the three channels respectively. The unmodeled and parametric uncertainties, coupling effects and the external disturbances are regarded as the total disturbance and are estimated and compensated by the extended state observer in the real time. Through the stability margin tester tuning method, the expected stability margin and transient performance are guaranteed for the three channels. Moreover, through the command transformation according to the flight dynamics of the hypersonic vehicle, the control schemes for the pitch, yaw and roll angle can be applied to the control of the angle of attack, the angle of sideslip and the bank angle directly, thus realizing a unified control frame for all the attitude angles. Simulation results demonstrate the satisfactory tracking and disturbance rejection ability of the proposed methods.
    AUV Horizontal Hover Control Based on Position-speed Closed Loop
    MA Yan-tong, ZHENG Rong, YU Chuang, AN Jia-yu
    2019, 26(10):  1810-1814. 
    Asbtract ( )  
    Related Articles | Metrics
     A kind of position-speed closed loop control method is designed for the heavy AUV (Autonomous Underwater Vehicle) with long rotary shape to realize AUV's horizontal hovering function. Aiming at the weak maneuvering and slow time-varying characteristics of AUV in hovering process, the speed feedback is introduced based on position closed-loop control, and the target speed is obtained by linear combination of distance deviation and sailing speed, which then can control the main propeller rotating speed. Based on the analysis of AUV hydrodynamic characteristics and control variables, the dynamic control method is designed, and the parameter configuration is completed to realize the stable hovering at the target point. Finally, through the lake trials, it is concluded that AUV can be stabilized within the target point of 4 m. Compared with the traditional position closed-loop control, the hover range is greatly reduced, and large adjustment caused by the inertia overshoot is improved, which verify the effectiveness of the linear position-speed closed loop control method.
    Soft Sensor of Ball Mill Load Parameters Based on Multi-Mode Transfer Learning#br#
    #br#
    HE Min, ZHI En-wei, CHENG Lan, YAN Gao-wei
    2019, 26(11):  1994-1999. 
    Asbtract ( )  
    Related Articles | Metrics
    It is necessary to monitor multiple load parameters during the operation of wet ball mill. However, the change of working condition will lead to the fact that the real time data and the modeling data do not satisfy the assumption of independent and identically distributed. In order to solve the deterioration of model performance caused by the change of probability distribution of historical data and real time data under multiple conditions, and the correlation between the load parameters cannot be fully considered by the traditional soft sensing model. The transfer learning strategy and multi-task learning mechanism is introduced to establish a soft sensing model of wet ball mill load parameters based on multi condition transfer learning. Firstly, the joint distribution adaptation is used to fit the marginal and conditional distribution in the dimension reduction process. Then, the mill load parameters are predicted by multi-task least squares supports vector machines. Experimental result indicates that the performance of the proposed method is superior or at least comparable with existing benchmarking methods, can solve the problem of soft sensor under multiple loading condition.

    The Two-layer Classifier Model and its Application to Personal Credit Assessment

    CAO Zai-hui, YU Dong-xian, SHI Jin-fa, ZONG Si-sheng
    2019, 26(12):  2231-2234. 
    Asbtract ( )  
    Related Articles | Metrics
    With respect to the different specific problems, the prediction accuracy of traditional machine learning methods often exist difference, while ensemble learning achieves significant improvement in classification performance by combining several of base classifiers. First, the basic idea of ensemble learning is briefly introduced, and the advantages of Stacking over the traditional classical ensemble algorithms are analyzed. Then, based on the Stacking framework, the two-layer classification model is developed to evaluate the personal credit by using the UCI datasets. Finally, the proposed method is applied to the empirical analysis, and the results show that compared with the single machine learning method of SVM, RF, ANN, GBDT and simple average ensemble, Stacking with two-layer classifier has a better prediction effect.
    Soft Sensor Modeling Based on Optimal Bounding Ellipsoid Algorithm with Penalty Factor
    SUI Lu-lu, HAN Dong-sheng, CHENG Lan, YAN Gao-wei
    2020, 27(1):  28-33. 
    Asbtract ( )  
    Related Articles | Metrics
    The predictive accuracy and generalization performance of soft sensor model are two important indexes of soft measurement modeling. Extreme learning machine algorithm which is based on optimal bounding ellipsoid (OBE-ELM) can overcome the shortcomings of the traditional extreme learning machines, such as low prediction accuracy and unstable prediction results, but the traditional OBE algorithm only minimizes the model error and does not consider the complexity of the model, which leads to over-fitting of the model. Aiming at the above problems, firstly, an optimal bounding ellipsoid algorithm (POBE) with penalty term is proposed for nonlinear systems with unknown but bounded noise, and the penalty term added to the objective function is used to suppress the magnitude of parameter growth and drive the unimportant parameter to zero gradually. Then, POBE is used for the optimization of ELM model parameters. Finally, the experiments were carried out on the channel parameter estimation and the continuous stirred tank reactor data sets to validate the effectiveness of POBE and POBE-ELM respectively.

    Research on Tracking Control Strategy of Maximum Efficiency for Wireless Power Transmission System

    ZHAO Qiang, CUI Chang
    2019, 26(2):  202-207. 
    Asbtract ( )  
    Related Articles | Metrics
    The high frequency AC power supply for wireless power transmission systems is provided by the class D power amplifier, and the receiving end uses the DC-DC converter to optimize load. Base on this research, the problem of reducing the transmission efficiency caused by the dynamic change of load condition, coupling coefficient and frequency offset is solved using the maximum power tracking control strategy, which includes frequency tracking and load tracking. The efficiency of the wireless power supply system is analyzed by the equivalent model of the transmitter and receiver circuit, and the optimal value of the equivalent load impedance matching is obtained. An integrated control strategy based on frequency tracking by phase locked loop and load tracking by searching for the minimum input power operating point for a given output power is proposed to keep the system output power and efficiency constant. The experimental results show that the proposed control strategy can automatically track the frequency and load changes, so that the system can always keep the resonant state, track and maintain the maximum energy transfer efficiency according to the load condition.
    Robust Iterative Fault-tolerant Control for Continuous Linear Time Invariant System
    YIN Chun-wu
    2020, 27(02):  234-239. 
    Asbtract ( )  
    Related Articles | Metrics
    A sufficient conditions for the convergence of D-type open-loop iterative learning controller is proposed for multiple input multiple output continuous repeat system in the presence of bounded external state disturbance and actuator failure. Under the conditions of the initial state is equal and the initial state exist bounded offset, based on λ-norm, this paper proposed the sufficient conditions for the convergence of the iterative learning controller respectively. It is proved that in the sense of λ norm, under the two conditions, the convergence conditions of the iterative controller are the same, only the upper bound of tracking error between the output of fault system and the expected trajectory is different. Based on Schur's complement principle, linear matrix inequality is given to determine the optimal control gain at a given convergence rate. Numerical simulations verify the effectiveness and feasibility of the proposed control strategy.
    Satisfaction Optimization Based Self-adaptive Adjustment of Process Alarm Thresholds
    CAI Yu, LI Hong-guang
    2019, 26(3):  417-422. 
    Asbtract ( )  
    Related Articles | Metrics
    The reasonable setting of process parameter alarm thresholds greatly influences the performance of an alarm system. In response to the limitations of traditional static threshold optimization, a novel satisfaction optimization based approach to self-adaptive adjustment of process alarm thresholds is explicitly introduced in this paper. Firstly, based on alarm treatment rates and alarm time recovery rates, a fuzzy reasoning strategy is employed to get the satisfaction index. Subsequently, the relations between the satisfaction index and FAR (false alarm rate), MAR (miss alarm rate) are used to calculate weights of FAR and MAR involved in the optimization objective function, in which kernel density estimations are conducted. Finally, numerical optimization methods are employed to achieve the optimal thresholds. Industrial data simulation results show that the proposed method has better environment adaptability and improved performance for alarm systems.
    Robust Controller Design of Fuzzy Singularly Perturbation Systems with Actuator Saturation
    WANG Yang, YANG Yi-yong, SUN Fu-chun, YANG Hong-jiu, MA Xi
    2019, 26(4):  638-644. 
    Asbtract ( )  
    Related Articles | Metrics
    This paper is concerned with the robust controller design of the continuous-time fuzzy singularly perturbation systems with actuator saturation. In order to solve the problem of the system with input saturation, a continuous-time singularly perturbation model subject to actuator saturation is given. A parallel distributed compensation (PDC) is used to design the controller and then the control system stability is proved. In addition, the ellipsoid and polyhedron contractive invariant conditions are derived with the help of the auxiliary feedback matrix. Then the stabilizing feedback controller gain to stabilize the system is obtained based on the linear matrix inequalities (LMIs). Furthermore, some necessary and sufficient conditions are given for single input systems. At last, a numerical example is given to illustrate the effectiveness of the designed protocol.
    Parallel Reactive Tabu Search for Solving Container Drayage Transportation
    LIU Zhu-jun, CHEN Zhi-kun, ZHANG Rui-you
    2019, 26(5):  825-828. 
    Asbtract ( )  
    Related Articles | Metrics
    The container drayage transportation problem is one hot point in international academic fields. A type of container drayage transportation problem considering multi-size containers is studied. Using a state-transition-based modeling method, this problem is formulated as a sequence-dependent multiple-traveling salesman problem with social constraints. Given the fact that personal computers with multiple cores of CPUs, including the computers with multiple CPUs, have been applied very widely, we design a multi-phase parallel reactive tabu search (PRTS) algorithm. The algorithm is validated extensively based on randomly generated instances. Results indicate that, compared with classical serial-implemented reactive tabu search algorithms, the PRTS algorithm can provide better solutions in shorter running time under the same computational environment.
    Fault-tolerant Control Method of Wire Controlled Four Wheels Steering Vehicle Based on Control Allocation
    ZHANG Shen-peng, ZHANG Deng-feng, LI Jun, WANG Zhi-quan
    2019, 26(6):  1035-1041. 
    Asbtract ( )  
    Related Articles | Metrics
     A kind of fault-tolerant controller with two-level structure is proposed in order to improve the handling stability and fault tolerance performance of wire controlled four wheels steering vehicles. It takes the front-wheel reference angle of the ideal vehicle model as the reference input. The basic control law of the top-level is designed based on the optimal control theory, to obtain the pseudo-control command. The control alloter of the bottom-level is then designed to distribute the front and rear wheel angles and drive the vehicle movement. The possible gain-type steering actuator faults are converted into the time-varying parameter perturbations for the control alloter design. A robust fault-tolerant control allocation algorithm is thus yielded, which can suppress the time-varying parameter perturbations and possible faults. The vehicle handling stability and fault tolerance are guaranteed. Finally, comparative simulation is executed for a four wheel steering vehicle time-varying 2-DOF model. The results indicate that the yielded controller based on the proposed fault-tolerant control allocation can effectively improve the vehicle handling stability and fault tolerance performance in the fault case.
    Research on Model Reference and Sliding Mode Control Strategy of Six Rotorcraft
    LI Wei-jie, WANG Si-ming, LIANG Xu-dong
    2019, 26(7):  1256-1261. 
    Asbtract ( )  
    Related Articles | Metrics
    To deal with the controlling complexity and strong state coupling for six rotorcraft, a attitude and trajectory control strategy based on model reference and sliding mode is proposed. First, on the basis of establishing a simplified kinetic and kinematic model of the six rotorcraft, a reference model with good performance is constructed by linear quadratic regulator(LQR) method, and the integral sliding mode is designed according to the pseudo inverse theory and the state error. Then, the attitude controller and trajectory tracking controller are designed in the presence of interference, and the Lyapunov stability theory is used to analyze and guarantee the stability of the closed-loop system. The simulation results show that the designed control system is superior to the general PID controller, which can achieve the attitude and trajectory control with a satisfied control performance.
    Stability Analysis of Switched Positive Linear System
    WANG Xiao-mei, MA Rui-cheng
    2019, 26(8):  1450-1453. 
    Asbtract ( )  
    Related Articles | Metrics
    For switched positive linear systems, the exponential stability analysis of switching signals with pre-given dwell time is discussed by using the time-varying linear co-positive Lyapunov function method. Firstly, by constructing the time-varying linear co-positive Lyapunov functions, sufficient conditions on the global exponential stability of the switched positive linear system are obtained under the dwell time switching signal with the upper and lower bound constraints. Secondly, sufficient conditions on the global exponential stability of switched positive linear system are also given by specifying the lower bound of the dwell time. All conditions can be written in the form of linear programming problems. Finally, an example is given to show the effectiveness of the proposed method. 
    Research on Improved Particle Swarm Optimization for BLDCM Speed Control System
    GENG Wen-bo, ZHOU Zi-ang
    2019, 26(9):  1636-1641. 
    Asbtract ( )  
    Related Articles | Metrics

    In the double closed loop speed control system of brushless DC motor(BLDCM), it was difficult to satisfy the application in high speed, high precision or large load disturbance using the PID parameters obtained with traditional optimization methods. Based on the research of standard particle swarm optimization (PSO), an improved PSO algorithm using orthogonal test mechanism was designed to optimize the PID speed controller, which solved the problem of slow optimization rate and easy to fall into local optimum in optimizing PID parameters with traditional PSO algorithm. By comparing the simulation results, it was indicated that the PID control method based on improved PSO algorithm had faster adjusting speed, smaller overshoot and strong anti-interference ability in the double closed loop speed control system of BLDCM. This method provides a new idea for the optimization of speed control system of BLDCM.

    Merging Maneuvers and Optimal Merging Control of Heavy-Duty Vehicles
    YUAN Hao-nan, GUO Ge
    2019, 26(10):  1815-1823. 
    Asbtract ( )  
    Related Articles | Metrics
    With the question of how to coordinate different trucks scattered on road to form a platoon, an optimal merging strategy of heavy-duty vehicles based on velocity and overall fuel consumption is proposed. Firstly,  based on the research of two heavy-duty vehicles, the merging condition, the optimal acceleration, the optimal merging speed and the location of the merging point can be obtained. Then the results are generalized and forming the general decision-making algorithm and the merging system controller design method. Numerical simulation and experiments show that the proposed method can greatly reduce the overall fuel consumption of vehicle fleets in fact.
    Actuator Fault Detection for Descriptor System: An Interval Observer Approach
    GUO Sheng-hui, ZHU Fang-lai, LI Ze
    2019, 26(11):  2000-2005. 
    Asbtract ( )  
    Related Articles | Metrics
    For the problem of actuator fault detection on uncertain descriptor system, an interval observer approach is investigated. An interval observer design method for descriptor system without actuator fault is discussed, and the problem is transformed into a Sylvester form by means of two transforms. By using the output of the interval observer and the output of the system, an actuator fault detector is built. The correctness and effectiveness are illustrated via a physical example.

    Path optimization algorithm of Multi-mode Automatic Guided Vehicle Based on MOWCA

    SU Shao-chun, GONG Yi-yu, FAN Song-hai, WU Tian-bao, LIU Yi-cen, LIU Xiao-jiang
    2019, 26(12):  2315-2400. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the path optimization effect of AGV, a multi model AGV route optimization method based on multi-objective wolf pack algorithm is proposed. Firstly, the AGV path planning problem is studied, and the multi-objective optimization function is given, and the two stage AGV path optimization system is designed; Secondly, the introduction of the wolves algorithm, using non-dominant wolves individuals for multi-objective optimization algorithm design, and using population individual density to maintain population diversity,, achieved the performance improvement of the multi-objective algorithm; Finally, the AGV programming performance of the algorithm is validated by the simulation experiments in the rectangular area obstacle, and the effective planning of the AGV running route is realized.
    Simulation and Study on Fluid Loop of Space Utilization Bypass Control Algorithm#br#
    #br#
    ZHENG Tong, ZHAO Li-ping, LIU Rong-hui
    2020, 27(1):  34-41. 
    Asbtract ( )  
    Related Articles | Metrics
    For the flow control problem of complex fluid looping system, a modified fuzzy PID controller which adapts different working conditions is designed. The lumped parameter method is used to build the simulation model. The flux and temperature model of fluid looping system is built based on fluid resistance and heat exchange theory. Other important modules of the system like centrifugal pump, stepping motor valve and liquid-to-liquid heat exchanger have been emulated at the same time. On basis of this, a fuzzy PID controller with valve status signal has been designed to decrease the effect of payload changing. Four different control algorithms, including the method described in this paper, have been compared together. The simulation results indicate the modified fuzzy PID controller has the best performance. Compared with traditional PID algorithm, it has excellent adaptability of nonlinearity, such us reducing 50 % maximum overshoot and 75 % setting time when valve of payloads has been closed.

    Short-term Wind Power Multi-step Forecasting Based on Interval Type-2 Fuzzy Logic Systems Method

    LI Jun, WANG Xing-hui
    2019, 26(2):  215-222. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at short-term wind power forecasting, a method composed of interval type-2 fuzzy logic systems (FLS) with non-singleton type-2 fuzzification is proposed. Taking into account the stochastic nature of the wind power, a forecasting model using an interval type-2 FLS with non-singleton type-2 fuzzification is firstly built, the back-propagation algorithm is then used to update the parameters including the input membership function, the antecedent and consequent membership function respectively, finally, the SVD-QR algorithm is applied to the results of the BP algorithm to determine the reduced set of fuzzy rules, the training process iterates until the forecast accuracy can meet the design requirement or reach the specified training epoch. The employed method is then applied to real-world wind power forecasting instances, under the same conditions, compared to the existing forecasting methods including support vector machine(SVM), type-1 FLS, interval type-2 FLS with singleton fuzzification, interval type-2 FLS with non-singleton type-1 fuzzification, etc. Experiment results confirm that the employed method can achieve better forecasting accuracy while the fuzzy rules are reduced.
    PLS Image Annotation Based on Dual Mode Semantic Space
    CAO Ying
    2020, 27(02):  240-245. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the accuracy of image annotation, and solve the problem of how to integrate text features and visual features of images, this paper puts forward an image annotation algorithm based on dual theme space. Firstly, the visual features and text annotation of image are represented as two views of the same object. Based on the multiple statistical analysis theory of partial least squares (PLS), the semantic dual relationship between the two feature spaces is considered to extract the dual shared semantic information. Then, a non-probabilistic annotation model is constructed on the symmetric space composed of dual theme. Finally, the predicted annotation vectors are calculated by the projection of visual features on dual theme space, the annotation texts of a new image are selected by setting the threshold. The algorithm performance is tested on the public data set of Core5K, experiments show that the proposed algorithm based on dual mode semantic space can effectively improve the performance of image annotation and the number of annotation accuracy.
    Indoor Unmanned Aerial Vehicle (UAV) Obstacle Avoidance System Based on Fuzzy Expert Decision
    YU Jian-jun, ZHAO Shao-qiong, ZHENG Yi-jia, RUAN Xiao-gang, WU Peng-shen
    2019, 26(3):  423-430. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to realize all-round obstacle avoidance planning of quad-rotor unmanned aerial vehicles under the indoor environment, the paper builds a three-dimensional detector by using ultrasonic sensors to detect obstacles so as to avoid the impact of visible light and reduce the system cost. For the problems of fuzzy rule “exploration” and decision conflicts caused by multi-sensor configuration, the paper combines the multilevel fuzzy controller with the expert system to make three-dimensional obstacle avoidance decisions. It sets up the three-dimensional obstacle avoidance decision controlling system based on the fuzzy expert system and designs the fuzzy controller and expert system. The validity of the method is verified by MATLAB simulation.
    Roughness Measurement of Face Milling Surface Based on Hough Transform and GLCM
    MIN Li, WANG Zhe, DONG Shuai
    2019, 26(4):  645-651. 
    Asbtract ( )  
    Related Articles | Metrics
    A non-contact roughness measurement method of the face milling surface is studied in this paper，which is based on computer vision theory. The face milling surface image is obtained by the image collection system and is preprocessed. Using Hough transform, the image is rotated to ensure the texture direction is vertical downward. Therefore, we can compute GLCM texture parameters only on this single direction, thus the computing time is saved greatly. The four GLCM texture parameters are extracted as the roughness characteristics of face milling surface. BP neural network is used to model the relations between the GLCM texture parameters and the roughness Ra, and the roughness detection model of face milling surface is established. The experiment results showed that using GLCM based on Hough transform can extract the roughness texture parameters quickly. The BP network model can measure the roughness of face milling surface precisely.
    Stability Analysis of a Predator System with Strong and Weak Allee Effect
    YI Na, LIU Peng
    2019, 26(5):  829-834. 
    Asbtract ( )  
    Related Articles | Metrics
    The stability problem for a predator-prey system with strong and weak Allee effect is studied. The existence for the positive fixed points of the system with harvesting in the predator is investigated. The stability for the positive fixed points of the system is analyzed by the stability condition of Routh-Hurvitz. Finally, the figures of time response and phase portrait for the predator-prey system with strong and weak Allee effect are obtained by Matlab soft, respectively. For the varying capture force E, the bifurcation diagram and Lyapunov exponents of the system with the weak Allee effect are shown. The system has chaotic phenomena. The simulation results show the influence of the capture behavior on the stability of the system.
    The Design and Implementation of Antenna Servo Control for Vehicle Satellite Communication in Motion
    DAI Li, LI Jun, CHEN Jia
    2019, 26(6):  1042-1048. 
    Asbtract ( )  
    Related Articles | Metrics

     With the advent of the information age, satellite communications play an increasingly important role. As a typical representative of this field, SOTM (Satellite communication on-the-move) system has been widely used. Based on the analysis and study of servo control subsystem of the vehicle SOTM, a stepper motor servo control system is designed. The mathematic model of the actuator in the system is established by using the system identification toolbox in MATLAB. The servo system is simulated in MATLAB/Simulink. The speed-position dual closed-loop PID with disturbance compensation control algorithm is designed. The experimental results show that the proposed stepping motor servo control system can significantly suppress the disturbance of the carrier and meets the performance requirements.

    Balance Control for a Two-bared and Two-wheeled Vehicle Robot under Synchronously Bars Turning
    HUANG Yong-hua, WANG Chang-sheng, HE Shu-tong, ZHUANG Wei, ZHANG Jie
    2019, 26(7):  1262-1269. 
    Asbtract ( )  
    Related Articles | Metrics
    This paper presents the strategy to balance a two-bared and two-wheeled vehicle robot under synchronously turning its two bars. Dynamics model of the vehicle robot was established by Chaplygin Formulation. As for the balance controller, the running angle of the robot's wheel was linearized by partial feedback linearization method, and the running angle of the two wheels was taken as input. Moreover, considering the undesirable influence of the drifting controller parameters, a fuzzy algorithm was adopted to tuning these parameters online. On the condition that the handlebars being turn between ±45°, the mode switching numerical simulations of the track-stand motion and the forward movement were performed. The results show that, the pitch angle of the frame can rapidly turn back to a balanced state, and the controller with the fuzzy algorithm has shorter adjustment time and smaller overshoot. Physical prototype experiments further testify the effectiveness of the controlling strategy.
    Research on Model Reference Adaptive Control Strategy for Static Pressure Detection System
    LONG Kai, HUANG Xue-mei, TAO Li-ming, ZHANG Lei-an, YUAN Guang-ming, Liu Wei-sheng
    2019, 26(8):  1556-1560. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the precision and response speed of the 1000-hour static pressure test of FRP pipe, and to realize the real-time tracking of the target, a model reference adaptive control strategy based on generalized-error was proposed. Firstly, the mathematical model of static pressure detection system was established. Secondly, according to the Lyapunov stability theory, a model reference adaptive controller based on generalized-error was designed. Then，the Simulink simulation model was established, and the validity of the method was verified by comparing the adaptive control and PID control. Finally, the detection system platform was built, and the control effect was further validated by 1000 hours static pressure test. The results showed that under the adaptive control strategy, the actual pressure value of the detection system can follow the expected pressure value well, and the steady-state error does not exceed ± 0.03 MPa, which fully meets the static pressure detection accuracy requirements of FRP pipe.
    Sensorless Fuzzy Direct Torque Control System for PMSM
    ZHANG Hong-wei, WANG Hai-lin
    2019, 26(9):  1642-1647. 
    Asbtract ( )  
    Related Articles | Metrics
    For the issue that the efficient control of permanent magnet synchronous motor (PMSM) in electric vehicle, a fuzzy direct torque control (DTC) system without position sensor is proposed. Firstly, the fuzzy DTC is used instead of the traditional DTC to control the motor. Then, a fuzzy PI stator resistance estimator is proposed to estimate the stator resistance in real time, and compensate the stator resistance change caused by the environmental factors, so as to improve the estimation accuracy of the electromagnetic torque and stator flux in the fuzzy DTC. Finally, a model reference adaptive system (MRAS) is used to construct a motor speed estimator to realize the position sensorless control, so that it can reduce the system cost and improve the system reliability. The simulation results show that the proposed control system can precisely control the motor speed to follow the set value, and has good robustness.

    Sliding Mode Variable Structure Control for a Class of Underactuated Systems

    YU Tao, ZHAO Wei, YANG Kun
    2019, 26(10):  1824-1829. 
    Asbtract ( )  
    Related Articles | Metrics
    A novel sliding mode variable structure control scheme is proposed for a class of underactuated systems with two degrees of freedom. The whole system is decomposed into two subsystems, and the sliding surfaces of both subsystems are defined. The equivalent control of the first sub-sliding surface is utilized to construct the control input of the controlled system, and the sliding surface of the second subsystem is incorporated into the switching control law. The switching control of the controller is derived based on the sliding surface of the first subsystem, and then the ultimate sliding mode control law is obtained. The derived control law, which guarantees that both sub-sliding surfaces are asymptotically stable, can dynamically adjust its switching gain according to the variation of the second sub-sliding surface. The simulation results of an overhead crane system confirm the effectiveness and robustness of the proposed control scheme.
    Design of Terminal Sliding Mode Antisway Controller of Overhead Cranes with Disturbance Compensation
    CHEN Tian-yu, XU Wei-min, CHEN Xi, YUE Ya-wen
    2019, 26(11):  2006-2012. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to solve the internal parameter variation and external disturbance problem of 2-demensional underactuated overhead crane antisway control system, a terminal sliding mode controller with disturbance compensation is presented. In this method, the nonlinear disturbance observer is designed to estimate the uncertain dynamics of the system. And the terminal sliding surface is designed to make the tracking error converge to zero in finite time. At the same time, the chattering of the sliding mode controller is weakened. The stability analysis of the controller is given. The simulation results show the good performance of this control algorithm.

    Richardson-Lucy Algorithm Based Defocused Bubble Images Restoring

    Richardson-Lucy algorithm, gradient prior, blur kernel estimation, blind image restoration
    2019, 26(12):  2159-2163. 
    Asbtract ( )  
    Related Articles | Metrics
    As for flotation process based on machine vision, blurred images are restored based on image priors and Richardson-Lucy algorithm, considering blurred bubble images acquired by industrial camera. Firstly, blur kernel is estimated based on image priors in multi-scale. Then the Richardson-Lucy algorithm is improved to suppress the influences of saturated regions. Finally, the blurred image is restored utilizing estimated blur kernel and improved Richardson-Lucy algorithm. Experimental results demonstrate that compared with the Richardson-Lucy algorithm and other algorithms, the improved algorithm can restore image with better visual results and objective evaluation.

    Stabilization for Time-delay Rectangular Descriptor Systems

    LI Jie, LIN Chong, CHEN Bing, ZHAO Xin
    2020, 27(1):  42-48. 
    Asbtract ( )  
    Related Articles | Metrics
    This paper focuses on the stabilization problem for time-delay rectangular descriptor systems. To begin with, time-delay dynamic compensator is introduced for feedback compensator, a suitable Lyapunov-krasovskii functional is constructed and advanced integral inequalities are used to deal with the integral terms of functional derivatives, furthermore new stabilization condition for time-delay rectangular descriptor systems is obtained in terms of strict linear matrix inequality (LMI). Based on this stabilization condition, utilizing iterative linear matrix inequality algorithm, the relevant parameter matrices of dynamic compensator and feedback gains are computed. Finally, numerical example is given to demonstrate the advantage and effectiveness of the proposed method in this paper.

    Distribution Network Reconfiguration Based on Improved Genetic Algorithm Combined Second-order Cone Programing

    RONG De-sheng, DUAN Zhi-tian, HU Ju-shuang, LIU Jian-chen, ZHANG Lei
    2019, 26(2):  223-228. 
    Asbtract ( )  
    Related Articles | Metrics
    An improved genetic algorithm combined with second-order cone programing is proposed for distribution network reconfiguration to minimize power losses and eliminate voltage violations. The chromosome length is shortened by using the decimal genetic coding rule based on the loop. For eliminating the infeasible solutions generated during the optimization, the infeasible solution judgment method based on the switch loop-node matrix and the node layer strategy is adopted in this paper. Through the elite reserve and dynamic control mutation rate, the problem about the premature convergence of the genetic algorithm is effectively solved. Then, some equivalent conversion and relaxation are presented to cast the initial nonlinear power flow equation into a second-order cone model, which can reliably and efficiently solve the global optimality by using the available commercial software. Finally, case studies on IEEE 33-node test feeder are conducted and the results demonstrate the validity as well as effectiveness of the proposed method.
    Potato Shape Sorting Based on PCA-SVM Algorithm
    XU Wei-dong, ZHAO Zhong-gai
    2020, 27(02):  246-253. 
    Asbtract ( )  
    Related Articles | Metrics
    Potato shape is one of the important indicators of potato grading, this paper discusses a potato shape classification method based on machine vision technology, combined with the principal component analysis-support vector machine (PCA-SVM) algorithm. This method extracts the eigenvectors of eleven-dimensional in a single potato region，which can represent shapes, and principal component analysis (PCA) is used to reduce the dimension of the feature vector and extract the principal component features of the shape. Then, the principal component feature is brought into the support vector machine(SVM)for modeling, and the grid search method (GS) is used to optimize the parameters of SVM. In the detection, the images of potato samples were taken into the PCA model and the optimized SVM model by using the ten-fold cross validation (CV) algorithm to classify the potatoes. Experimental results show that the algorithm proposed in this paper has the higher sorting speed as well as the higher accuracy (97.3 %). The method is feasible for potato shape sorting and can be used for automatic potato grading.
    Key words: Potato, machine vision, shape sorting, principal component
    Economic Model Predictive Control of Variable-speed Wind Energy Conversation Systems
    CUI Jing-han, LIU Xiang-jie
    2019, 26(3):  431-439. 
    Asbtract ( )  
    Related Articles | Metrics
    For the wind energy conversation system (WECS), model predictive control (MPC) has become an effective way to reduce the cost of generating electricity and improve the utilization of energy. This paper presents a new control strategy, economic model predictive control (EMPC), to achieve control objectives of WECS with one on-line optimization problem, while realizing efficient switching between two operation regions. The simulation research of the 5MW WECS has been carried out aiming to compare the classical MPC and EMPC. The simulation results show that the EMPC can achieve the objectives while improving wind energy capture and reducing the fatigue load, especially in the switching process which has great significance on the improvement of the power quality and prolonging the service life of the facilities.
    Quality-Related Process Minitoring Based on Kernel Canonical Correlation Analysis
    REN Wei, SUO Han-sheng, JIANG Bai-hua, JIA Gui-jin
    2019, 26(4):  652-656. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at a large number of nonlinear problems in the chemical process, the main existing method is the combination of the kernel algorithm and the partial least squares (KPLS) algorithm. Compared with KPLS algorithm, the method of combining kernel algorithm and canonical correlation analysis (KCCA) algorithm can maximize the correlation between the two groups of variables to achieve better detection results. However, the current KCCA method cannot accurately decompose the data space into parts that are related and unrelated to the key performance indicator (KPI), thereby it ignores the fact that the remaining space still involves some information related to the KPI. In this paper, an improved KCCA is proposed. The method performs singular value decomposition (SVD) on the calculable loadings of kernel matrix, a projection model is obtained in which the kernel matrix is appropriately decomposed into KPI -related and -unrelated parts, and then two statistics are accordingly designed for fault detection. Finally, the Eastman Eastman (TE) process was used to verify the effectiveness and superiority of the proposed method.

    Design of Robust Controller for Rolling Based on State Space Model

    LI Ming-chun, TAN Shu-bin
    2019, 26(5):  835-842. 
    Asbtract ( )  
    Related Articles | Metrics
    For the rolling system, it should be a multi-variable, strong disturbance and coupled nonlinear system. As the precondition of ensuring the precision of strip thickness, it is necessary to ensure that the system is robust. The controller should be able to suppress the disturbance of the system and remain the system stable under the uncertain parameters. Taking into account the complexity of the system, this paper establishes a linear state space model of the hydraulic roller system, motor transmission and rolling process system for the deeper study of the relationship between the variables in the rolling process. Considering the complexity of the external disturbance, this paper chooses the  control strategy. MATLAB is used to solve the linear matrix inequalities. By selecting the appropriate performance index, the state feedback controller could be found. The simulation result shows that the state feedback control system has better robustness and performance index.
    Research on AGV Vision Precision Positioning Technology by an Improved Two-Dimensional Code
    LI Zhao, SHU Zhi-bing
    2019, 26(6):  1049-1054. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at the problem of traditional vision guided AGV(automated guided vehicle) positioning accuracy, an improved dimensional code precision positioning method is proposed. This method uses the two-dimensional code after the addition of frame processing as a positioning reference, the datum model is established by using the dimension of each frame sample. Through the extraction of the image of the two-dimensional code rectangle contour, determine the center coordinates of the rectangular region; then, the unified coordinate system can be got by coordinate rotation transformation. At last, calculating the error through the center point, achieve precise positioning. Experimental results show that, position once, it can improve the AGV positioning accuracy to 1 mm by this method.
    The Fluctuation Suppression Strategy of Photovoltaic and Energy Storage Integration Based on Vanadium Redox Flow Battery
    LI Xin, NI Xiao, QIU Ya, Zhang Hong
    2019, 26(7):  1270-1275. 
    Asbtract ( )  
    Related Articles | Metrics
    The abandonment of wind and light is the core issue of renewable energy development, and suppressing fluctuation with the combined power generation system of photovolatic and energy storage is a research hotspot. The combined power generation system of photovolatic and energy storage is the research object of this paper, which is used to study the interaction between PV output and energy storage. Stabilizing the photovoltaic fluctuation with vanadium redox flow battery can make the output power of the combined system smooth, which is based on the first-order low-pass filter and the moving average principle. The mathematical model of vanadium redox flow battery is established to verify that vanadium battery can stabilize fluctuations in different time scales. We did a simulation of 5kW/6h vanadium redox flow battery on Matlab/Simulink, and the simulation results show that the power output of the system of photovolatic and energy storage is smooth and the maximum power output is reduced under different filter time constants. This paper calculates the maximum power and the maximum energy requirement, which can provide the basis for the capacity configuration of each component of the combined power generation system of photovolatic and energy storage; And considering the battery characteristics, vanadium redox flow battery can also meet the requirements of the depth charge and discharge times.
    Output Voltage Optimization of Switched Reluctance Generator Based on Predictive Control
    LEI Xiao-ben, WANG Chuan-qi, LI Xue-feng
    2019, 26(8):  1490-1496. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the quality of the output voltage of the arc-transformer motor starting/power generation system and suppress the output voltage ripple, based on the analysis of the factors affecting the output voltage ripple of the switched reluctance generator (Switched Reluctance Generator, SRG), a nonlinear predictive control method for SRG based on the target state equation is proposed. To begin with, according to established nonlinear mathematical model of the SRG and the predictive control theory, the nonlinear predictive controller of the SRG is designed. Next, an extended state observer is designed to reduce the influence of external disturbance on the output voltage. Finally, the effect of the simulation verification algorithm is performed. The results of simulation show that compared with the PID control method, the nonlinear predictive control method makes the output voltage more stable and improves the robustness of SRG.
    Application of LMPC-PID Algorithm in Bed Temperature Control of CFBB
    GUO Wei, QIAO Dong-dong, LI Tao, LI Ming-jia
    2019, 26(9):  1648-1654. 
    Asbtract ( )  
    Related Articles | Metrics
     To deal with the features of bed temperature control of circulating fluidized bed boilers, such as large inertia, time-variant, multi-interference factors, a PID predictive control algorithm based on Laguerre function model is proposed. In this algorithm it changes the rolling optimization index of the predictive control algorithm based on Laguerre function model into a PID type structure. Combining the advantages of PID control and predictive control, this algorithm improves the speed, stability and robustness of the control system. The algorithm is applied to bed temperature control of circulating fluidized bed boilers, the simulation results show that it has good control quality.
    Composite DOBC & GMVC for a Class of Linear Stochastic Systems
    LIU Yun-long, ZHOU Ping, LI Ming-jie, Rong Jian
    2019, 26(10):  1830-1834. 
    Asbtract ( )  
    Related Articles | Metrics
    A novel control scheme combining disturbance observer technique and generalized minimum variance method is investigated for a class of linear stochastic systems. The unknown external disturbance is supposed to be generated by a exogenous system with perturbation, and the reduced-order and full-order disturbance observers based on minimum variance benchmark, which can be designed separately from the controller design, are constructed, respectively, for the cases that the state can be measured and the state cannot be measured. By integrating the disturbance observers with generalized minimum variance control laws, the disturbances can be rejected and the desired dynamic performances can be guaranteed. Finally, a numerical example is proved to show the effectiveness of the approach.
    Research of Modeling with Small Sample for Complex Problem
    FENG Guo-qi, CUI Dong-liang, ZHU Kai-quan, ZHANG Qi
    2019, 26(11):  2013-2018. 
    Asbtract ( )  
    Related Articles | Metrics
    The problem of small sample size for machine learning is caused by the test cost of complex production, and experiment should be well designed to maximize the information under the size constraint of data set. This paper prompts a sample selection method for multiple linear regression (MLR): Hamming distance is used to evaluate the similarity of samples and depth-first strategy is employed to generate a data set with specified size by max-min Hamming distance, and the selected data set is used to evaluate the generalization performance. Finally a case of high pressure turbine disc design is used to verify this strategy, the result shows that the proposed strategy reduces experiment cost with necessary accuracy.

    Research on Viscosity Compensation Method Based on Improved Binary-tree Model

    ZHANG Hao, WANG Xin, WANG Zhen-lei
    2019, 26(12):  2164-2170. 
    Asbtract ( )  
    Related Articles | Metrics
    An improved Binary-tree model is proposed to solve the stiction problem, and the fuzzy internal model Smith control method and the improved Knocker signal compensation method are used to compensate this problem. Firstly, improve its deficiencies when the dynamic friction is 0. And increase the judgment condition of the input signal rate, modify the model of improved two binomial tree model. The fuzzy internal model Smith control method can achieve the parameters of the system, reduce the shock, compensation stiction problem; adding threshold in Knocker signal at the same time, also can reduce the frequent movement of the valve from theory, increase the service life of the valve. The simulation results show that the improved model can effectively describe the viscous characteristics, and the two methods can effectively compensate the viscous problem and improve the performance of the system.
    Observer for Time-Varying Sliding Mode Synchronous Control of Double-Container Overhead Crane System
    YUE Ya-wen, XU Wei-min, CHEN Tian-yu, CHEN Xi
    2020, 27(1):  49-56. 
    Asbtract ( )  
    Related Articles | Metrics
    To deal with the problems such as modeling inaccuracy, internal parametric perturbation and external disturbance commonly existing in double-container overhead crane system, this paper adopts the cross-coupling strategy and propose a method of nonlinear disturbance observer for time-varying sliding mode synchronous control of double-container overhead crane system. First, using time-varying sliding mode control ensures the global robustness of the controller. Then, the nonlinear disturbance observer to observe is employed the lumped disturbances and compensate the disturbances to the controller. Besides, a variable gain reaching law is proposed which can dynamically adapt to the variations of the control system, and effectively reduce chattering on control input and shorten approach time. Finally, the asymptotic stability of controller is verified by Lyapunov theory, the simulation results show the effectiveness of the proposed method, and the controller ensures good performance in the presence of unknown disturbances.

    Aeroengine Adaptive PID Control Based on Hybrid Artificial Bee Colony Algorithm

    CHEN Yu-han, XIAO Ling-fei, LU Bin-bin
    2019, 26(2):  229-235. 
    Asbtract ( )  
    Related Articles | Metrics
     In view of the fact that the traditional artificial bee colony (ABC) algorithm has a slow convergence speed and traps into local optima easily, a new hybrid artificial bee colony (HABC) algorithm is proposed, which improves the optimization performance in three aspects: selection mechanism, neighborhood search mechanism and diversity of solution vectors. Aimed at the aeroengine control system, an online adaptive PID controller of optimum is designed based on this algorithm. In the control process, the parameters of PID controller are optimized constantly by HABC algorithm so that the aeroengine controller can adaptively obtain the time-varying optimal parameters according to the current system working status. Simulation results show that the aeroengine online adaptive PID controller implements the time-varying optimum of PID controller parameters, which insures that the closed loop system has good dynamic performance as well as strong robustness.
    Hybrid Fruit Fly Algorithm for Distributed Heterogeneous Parallel Machine Scheduling
    HUANG Yuan-yuan, QIAN Bin, WU Li-ping, HU Rong
    2020, 27(02):  254-263. 
    Asbtract ( )  
    Related Articles | Metrics
    The scheduling problem model of distributed heterogeneous parallel machine is presented in the background of the actual production problems in industrial production. Then, a hybrid fruit fly optimization algorithm is designed to minimize the maximum completion time of the considered problem. Firstly, the competition mechanism is added in the initialization phase of the algorithm, which effectively improves the quality of the initial solution. Secondly, the adaptive search radius is introduced in the smell search stage to effectively search the solution space. Finally, the three-phase local search is integrated into the update phase of the algorithm, so global search and local search can achieve a better balance. Simulation experiments and algorithm comparisons verify the effectiveness and robustness of the proposed hybrid fruit fly optimization algorithm.
    Discrete-time Model Identification and Sliding Mode Control for Continuous Stirred Tank Reactors
    GUAN Xing-chen, LIU Hang, MA Lu-ning, ZHAO Dong-ya
    2019, 26(3):  440-447. 
    Asbtract ( )  
    Related Articles | Metrics
    This research mainly aims at the simplified model of the complex continuous stirred tank reactor (CSTR) chemical process, which presents a discrete-time state space modeling approach based on a large number of input and output data, by using the least square identification method. According to the model, a discrete-time nonlinear sliding mode controller is designed, and the stability is proved. In the simulation, the proposed approach is compared with the traditional PID, which illustrates the validity and practicability of the proposed approach.
    Flow and Pressure Fast Control of Water Flow Standard Facility
    DANG Shi-zhong, SUN Li-jun, TANG Bing, ZHANG Tao
    2019, 26(4):  657-663. 
    Asbtract ( )  
    Related Articles | Metrics
    Mutual coupling between the flow and pressure regulation reduces rapidity of the control system. To address this, taking water standard facility as an example, the coupling between flow and pressure regulation is analyzed. Regulating valve opening and inverter frequency are selected as the main control variable of the flow and the pressure respectively. And a quick flow and pressure control method based on back-propagation(BP) neural network and PID control is proposed. The established neural network model achieves a high predicting precision. The relative error of valve opening prediction is within ±5 % and that of inverter frequency is within ±0.6 %. The experimental results indicate that the control combining BP neural network and PID can achieve a faster flow and pressure regulation: compared with the serial PID control, the regulation time is decreased by 38.5 %~87.3 %, and compared with the parallel PID control, that is decreased by 25.4 %~83.7 %.
    Study on the Equivalence Between Soft-Constraint Approach and Fuzzy Method in Model Predictive Control
    XU Jun, SUI Yi, LUO Xiong-Lin
    2019, 26(5):  843-850. 
    Asbtract ( )  
    Related Articles | Metrics
    In chemical processes, there are constraints imposed on the inputs and outputs. For constraints on the outputs, which are not hard, i.e., the constraints can be violated to some extent, we can use fuzzy membership functions to describe the violation. However, in general, the fuzzy model predictive control problem is hard to be solved. Another method dealing with the violation of the output constraints is soft constraint method, i.e., allow the constraints on the outputs to be violated and then penalize the violation. For one kind of fuzzy model predictive control problems with specific membership functions and aggregation operators, we can transform it to a soft constraint optimization problem, which is basically a quadratic programming. Hence the computational burden is largely reduced. The simulation results verify the equivalence and the savings in the computational burden.
    Research on Tracking Control Strategy of Uncalibrated Robot Visual Servo System
    CHEN Mei, CHE Shang-yue
    2019, 26(6):  1055-1059. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at the un-calibrated robot Visual Servo system of the eye in hand structure, a fuzzy control strategy with image feature as feedback is proposed to track the moving objects in the plane. The control strategy is simulated by Matlab and Robotic toolbox. The motion tracking system of an un-calibrated robot Visual Servo system is constructed based on three axis Cartesian coordinate system robot, camera and computer. The working principle of the system is as follows: the current image is collected by the camera, then the relative position of the object and the end of robot is measured by Matlab image processing, the action state of the robot is controlled by the fuzzy controller. According to the image real-time feedback from camera, constantly correct the deviation, and ultimately achieve stable tracking. The experiment and simulation experiment of physical crawling verify the feasibility and practicability of the system. It provides a new way to improve the rapid crawling of industrial automation production line, and paves the way for the follow up of un-calibrated servo system.
    The Aggregation Based Model Predictive Control Approach for Inverter
    GAN Zhong-xue, CHEN Wen-bo, XU Yu-li, LI De-wei
    2019, 26(7):  1276-1283. 
    Asbtract ( )  
    Related Articles | Metrics
    Inverters are the important devices for the modern power systems. The control performance of the inverters has influence on the efficiency and quality of the power systems. In this paper, an aggregation based model predictive control method (AMPC) is presented in three-phase three-wire voltage source inverter control. The AMPC can decrease computational complexity significantly, which makes the online computation fast and feasible. The cumulate incremental state space model (CISS-Model) is set on the d-q rotation coordinate, which is able to transfer the control as a constant reference tracking problem, eliminate the steady state error and improve the control accuracy. Simulation results demonstrate that the proposed strategy can eliminate the steady state error and has good dynamic characteristics. The calculation amount is as much as PID control.
    Study on Grid-connected Control for Two Interconnected Generators
    LIU Jian-hui, QUAN Xiao-chen
    2019, 26(8):  1578-1584. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to regulate frequency and voltage of photovoltaic generator flexibly and fast for interconnected system, the grid-connected power control method of the photovoltaic power generation unit and the synchronous generator is analyzed, virtual synchronous generator (VSG) control method with minimum adjustment parameter design is proposed. The least-parameter frequency modulator has a first-order inertia characteristic, which can solve the resonance problem when the two-machine interconnection is connected to the grid. The transient operation of the nonlinear reactance simulation system in the VSG impedance model achieves the accuracy and flexibility of the VSG adjustment during the transient transition of the interconnected system. The simulation results confirm the feasibility and effectiveness of the SVG structure with least regulating parameters.
    Multivariable nonlinear RBF neural network predictive control based on TSA
    JIANG Xue-ying, GUO Ying, SHI Hui-yuan, SU Cheng-li
    2019, 26(9):  1655-1660. 
    Asbtract ( )  
    Related Articles | Metrics
    To deal the difficulty for online real-time computing the nonlinear equation with the present nonlinear predictive control method, a multivariable nonlinear neural network predictive control algorithm based on tree and seed algorithm (TSA) is proposed. This algorithm adopts the multi-RBF neural network to construct the nonlinear system, which is used as the predictive model. The optimal control law of the nonlinear predictive control system is searched online using TSA, thereby avoiding the problem of complex nonlinear optimization for directly solving the control law. Simulation results of CSTR show that the proposed control scheme has excellent tracking and resisting disturbance abilities.
    Dual-Loop Adaptive Tracking Control with Physical Constraint
    Nonlinear system, adaptive control, control saturation, dual-loop tracking control
    2019, 26(10):  1835-1842. 
    Asbtract ( )  
    Related Articles | Metrics
    A dual-loop robust tracking control method is proposed for the tracking control of generalized second-order nonlinear systems with variable parameters and bounded state and control inputs. The system is decomposed into two independent subsystems by introducing virtual tracking controller, the outer loop virtual controller tracks the input globally asymptotically and generates the inner loop virtual input, the inner loop adopts adaptive control method to realize robustness which caused by parameter’s perturbation, external disturbance and exceed saturated amplitude, and to ensure the exponential convergence of the virtual input. Dual-loop adaptive tracking controller can satisfy the tracking accuracy and robustness to uncertainties under bounded state and control inputs. The system with dual-loop tracking controller has higher reliability than the one with backstepping controller. Numerical simulation of spacecraft attitude tracking control problem verifies the validity of the method.

    Research on Low Speed Control Strategy of Hybrid Excitation Synchronous Machines

    GUO Dong, ZHANG Bo, WANG Wei, QI Xiao-ye
    2019, 26(11):  2019-2024. 
    Asbtract ( )  
    Related Articles | Metrics
     In order to improve the load-bearing ability of the hybrid excitation synchronous machines at low speed and reduce the influence of load disturbance and variable speed motion on the control system, a hybrid control strategy based on load torque observer for excitation current given strategy and q-axis current feedforward compensation strategy is presented. And, a reduced-order observer is used to identify the load torque online. The identified load torque is used as one of the criteria for judging whether the hybrid excitation synchronous motor needs to increase the torque output. At the same time, the identified load torque and its rate are used as the excitation current reference inputs and q-axis current feedforward compensation, which can improve the load-bearing ability of the hybrid excitation synchronous motor. And, the control strategy can overcome the effect of time-varying load on control performance. Simulation results show that the proposed low speed control strategy can effectively improve the dynamic characteristics and enhance the robustness of the hybrid excitation synchronous machines speed control system.

    Control of Molecular Weight Distribution Based on Finite Order Moments

    WU Hai-yan, CHEN Yu, WANG Jing
    2019, 26(12):  2171-2175. 
    Asbtract ( )  
    Related Articles | Metrics
    Based on the statistical principle, it is proved that the cutoff moment problem of the molecular weight distribution (MWD) has a unique solution in the polymerization reaction object, that is, moments of the distribution function correspond to the distribution function, and all moments of the MWD can be deduced from the finite lower order moments. The number of independent lower order moments is equal to the independent parameters of the distribution function, which provides the theoretical basis for the distributed function of finite order moment control. The correctness of above conclusion is testified by simulation results.
    Establishment of BA Network Model Based on Adaptive Algorithms and Clustering Analysis of Network
    DUAN Jia-yong, GUO Fang, ZHANG Xiao-yu, BAI Ke
    2020, 27(1):  57-63. 
    Asbtract ( )  
    Related Articles | Metrics
    BA model is a classic scale-free network model, which has some small world characteristics, but the clustering coefficient approaches zero with increasing number of points. In order to further optimize the average path length and clustering coefficient of BA network model, an improved scale-free network model based on adaptive algorithm is designed. The improved model optimizes the correlation degree of network nodes and the system. By calculating the optimal value of the correlation degree and the value of each parameter in the network Thus, the ideal network model is obtained. Through the mathematical analysis of the adaptive algorithm, the average path length of the system is the convergence state with conditions. The simulation results show that the improved network model is further optimized in terms of average path length and clustering coefficient. Unlike the BA scale-free network, the improved model has obvious clustering characteristics and is more accord with small world network characteristics.

    A Method with Adaptive Seed Point Substitution for Counting Overlapped Cell

    CHEN Ming, YANG Hui-zhong
    2019, 26(2):  236-240. 
    Asbtract ( )  
    Related Articles | Metrics
    Cells of microscopic cell images are often adhesive. In order to count, it is usually necessary to find the seed points of the adhesion cells accurately. This paper proposes an algorithm of counting the overlapped cells based on pixel block scanning with good adaptability. On the basis of determining the area of the maximum and minimum in connected sections, the length of the maximum and minimum rectangular pixel block with same width side is determined. And then, the two value image is scanned by the maximum pixel block with width of side automatic decreasing from left to right, from top to bottom. The area matched to a near-circular pixel block is replaced with a seed point to get a seed point image and counting. A lot of experiments show that the method proposed in this paper has a significant effect on counting overlapped cells with different areas and has good adaptability.
    Application of Improved HVD in Fault Diagnosis of Rolling Bearings
    XIAO Pu, YIN Li
    2020, 27(02):  264-270. 
    Asbtract ( )  
    Related Articles | Metrics
    Due to end effect exists in Hilbert transform and low pass filtering of Hilbert vibration decomposition，an improved Hilbert vibration decomposition method is proposed. Mirror-symmetric extension method is adopted in signal preprocessing in Hilbert transform, low pass filtering and synchronous detection, and the end effect caused by Hilbert transform and low pass filtering was eliminated. Subsequently, instantaneous frequency obtained by Hilbert transform and low pass filtering process was regarded as reference frequency. Finally, several components with different amplitudes were obtained by using synchronous detection and iterative operation. The simulation signal and experiment data generated from roller bearing demonstrated that the proposed method has excellent performance in vibration signal decomposition and end effect suppression, and it can effectively diagnose the roller bearing defect appeared on inner and outer race. So it has certain practical engineering application value.
    Research on Remaining Useful Life Prediction of Mechanical Systems Based on Fusion of Multi-model Particle Filter
    JIANG Dong-nian, LI Wei
    2019, 26(3):  448-453. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at the problem of performance degradation and life shortening caused by long-term use of mechanical systems, a life prediction method is designed by using the particle filter algorithm, which can provide theoretical basis for timely maintenance of mechanical equipment and prolong the life of equipment. Firstly, a multi-model method is used to model the operation process of mechanical equipment, which overcomes the shortcoming of the traditional single model which is difficult to describe the life cycle of mechanical equipment. Secondly, by using the particle filter algorithm and system model switching matrix, the remaining service life of the system can be predicted. Finally, in order to improve the prediction accuracy, a compensation algorithm for predicting deviation is designed to achieve unbiased prediction. Taking the crack growth of high-speed train axle steel as an example, the correctness and effectiveness of the proposed method are verified by simulations.
    Research on the Control Room Design Based on Ergonomics
    CHEN Yuan
    2019, 26(4):  664-669. 
    Asbtract ( )  
    Related Articles | Metrics
    It aims to study the design method for the human-machine-environment of the control room, which can be used to improve the usage of the machine and the work efficiency and comfort of the operators. Based on ergonomics analysis of the requirement focused on human, the design elements of “machine” are divided into styling basic features, layout, size and control design. The design elements of “environment” are divided into physical environment, material environment, and emotional environment. It summarizes design rules and methods for these elements and makes them meet the requirement of human. The design rules and methods will offer effective reference and suggestion for the ergonomic design of the control room.
    Numerical Simulation of a PID Decoupling Control System for Temperature and Relative Humidity in an Air-conditioning Room
    ZHU Qi-ran, LI Shao-yong, LI Peng-bo
    2019, 26(5):  851-858. 
    Asbtract ( )  
    Related Articles | Metrics
    For air-conditioning systems having dynamics of large time-delay and inertia together with strong coupling between the regulation of temperature and relative humidity, and so on, a PID decoupling control system is proposed in this paper by synthesizing the air-conditioning processing and the technologies of PID and the decoupling control method. this PID decoupling control system for temperature and relative humidity in an air-conditioning room is configured and its numerical simulation is carried out via MATLAB software. The results show that the proposed PID decoupling control system using the PCTT matrix method is feasible in theory. Compared with the traditional multi-loop PID control system based on the Ziegler-Nichols setting method, for the temperature and relative humidity of the same plant, the proposed PID decoupling control system using the PCTT matrix method can eliminate the mutual influence existing in the adjustment channels between temperature and relative humidity and its control performance is better than that of the non-decoupling PID control system.
    Based on Hybrid Fisher and Fuzzy Algorithms to Improve Classification Accuracy of EEG-Based SSVEP Brain Signals 
    DU Xiu-lan, ZHANG Jin, MAO Xiao-qian, ZHANG Kai-li, LI Wei
    2019, 26(6):  1060-1067. 
    Asbtract ( )  
    Related Articles | Metrics
     In order to improve the classification accuracy of electroencephalographic based on the steady-state visual evoked potential (SSVEP) in brain computer interface (BCI), a new classification algorithm combining Fisher and Fuzzy is proposed in this paper. First, the algorithm uses Fisher to obtain the optimal projection direction and the threshold value for the EEG signals. Second, calculate the distance d and fuzzy it. Finally, the classification result is obtained by fuzzification and defuzzification process. The classification algorithm overcomes the shortcoming that the samples in the ambiguous area cannot be accurately classified by using a single Fisher classifier in SSVEP for multiple classification problems. In the three, four and five-classification based on the SSVEP, the classification algorithm proposed in this paper has achieved 94.72 %, 92.18 % and 86.08% average classification accuracy that are higher than using a single Fisher classifier achieved 90.07 %, 80.60% and 74.42%. Faced with the low separability data set, the algorithm can significantly improve the classification accuracy.
    Traffic Signal Optimization Control in Five-road Intersection Based on Artificial Fish Swarm Algorithm
    TANG Min-an, DONG Hai-long, CHENG Hai-peng
    2019, 26(7):  1284-1290. 
    Asbtract ( )  
    Related Articles | Metrics
    : The traffic signal control system plays a key role in the road network, and its control performance directly affects the traffic safety and delay time in the intersection. Traditional control in five-road intersection does not have the ability to adjust itself, which wastes green time. This paper adopts a method that use artificial fish swarm algorithm (AFSA) to optimize dynamic-fuzzy neural network (D-FNN) to achieve multi-phase and variable phase sequence intelligent control in five-road intersection. Taking the reciprocal of average vehicle delay as the food concentration of AFSA, and the weights and thresholds of the dynamic-fuzzy neural network which need to be modified are used as the individual state of artificial fish. A set of optimal dynamic-fuzzy neural network parameters are obtained through iterating and updating. After doing simulation analyses in the case of different rates of vehicles arrival, the result shows that this method is better than the traditional control in automatically adjusting the signal cycle, and it reduces the average delay of vehicles for about 11%.
    Super-heated Steam Temperature Control System of Power Plant Based on Fuzzy Logic Controller and SPSO
    SHUAI Hai-yan
    2019, 26(8):  1561-1565. 
    Asbtract ( )  
    Related Articles | Metrics
    For the issues that the accurate control of the superheated steam temperature in thermal power plant boiler, a feedforward - feedback control system based on fuzzy logic control (FLC) is proposed, and construct a two-stage temperature regulation mechanism of feedforward and feedback. The feedforward FLC controller outputs a spray flow rate signal based on the feedwater flow rate and the fuel flow rate for the middle section superheater and the rear stage superheater control module respectively. The feedback FLC controller outputs a spray flow rate signal based on the temperature error and the error change rate between the superheater output steam temperatures with the reference. And the simplified particle swarm optimization (SPSO) is used to optimize parameters. Then, the two spray flow rate signal is fused, so as to accurately control the spray control valve, and stable steam temperature to the reference value. The simulation results show that the proposed FLC control system can control the temperature quickly and efficiently, and has good robustness to the load change.
    Disturbance Rejection at the Output of Grid-connected Inverter based on H-infinity Control
    XIAN Yan-hua, WANG Shi-qiang, JIANG Ming-xuan
    2019, 26(9):  1661-1666. 
    Asbtract ( )  
    Related Articles | Metrics
    To reject disturbances at the output of grid-connected photovoltaic system such as load changes, grid voltage fluctuations and external noise, a control system model of the grid-connected inverter is constructed based on H-infinity theory. In this model, grid voltage, reference current and external noises are used as input signals, and the output current of the inverter is used as the output feedback signal to indirectly control the grid current. Meanwhile, a harmonic compensator with damping resonance is used to realize the grid current harmonics suppression. The simulation results show the grid current controlled by the designed H∞ controller can meet requirements of total harmonic distortion rate less than 5 % , same frequency and phase with grid voltage when the load varies, grid voltage waves and noise occurs at the output. The comparison of PI control, Quasi-PR control and H∞ control simulation results shows that the grid connected current controlled by H∞ control has better harmonic performance, and the robust performance of the PV system is improved.
    Reduced-order Observer-based Backstepping Control of Permanent Magnet Synchronous Motor
    LAN Yong-hong, CHEN Qian, WANG Liang-liang, CHEN Cai-xue
    2019, 26(10):  1843-1849. 
    Asbtract ( )  
    Related Articles | Metrics
    For the speed tracking control problem of permanent magnet synchronous motor (PMSM), an reduced-order observer-based back-stepping speed tracking control method is presented. Firstly, the output value of the rotational speed of the PMSM is used to construct a full dimensional Luenberger observer. By using Lyapunov stability theory, the linear matrix inequality (LMI) based design method of observer is obtained. Then, based on the full order observer, a reduced order observer is designed by using matrix decomposition techniques. To realize the high precision tracking for the motor speed, a back-stepping control strategy of the closed-loop system is also proposed. Finally, the effectiveness of the proposed method is verified by numerical simulation. The simulation results show that the designed controller can make the output of the system quickly track the reference speed and has high tracking accuracy.

    The Vehicle Interior Sound Quality Prediction and Analysis Based on RBF Neural Network

    ZHANG Yong, WANG Kun-xiang, OU Jian, LIU Ya
    2019, 26(11):  2025-2030. 
    Asbtract ( )  
    Related Articles | Metrics
    Considering the sound quality of the special vehicle, a radial basis function (RBF) neural network method is proposed for calculating the weight and predicting subjective evaluation results concerning the influence of the objective evaluation parameters. First, three different types of special vehicles were tested on the road, and a subjective evaluation test was carried out to calculate the objective evaluation parameters of the sound quality by using the grade method. Then, the RBF neural network model was established for sound quality prediction inside the vehicle. The objective evaluation parameters are regarded as the input of RBF neural network model, and the subjective evaluation results as output, and the good consistency is obtained by comparing the simulation result with the subjective evaluation value of sound quality. Finally, the connection weight between the network layers was applied to calculate the influence weight of the objective evaluation parameters on the subjective irritability. The results show that the sound quality of the vehicle is mainly affected by the objective parameters of the overall loudness, loudness and speech interference level(SIL-4).

    Adaptive Robust Control of Chinese Medicine Sugar Precipitation

    DUAN Hong-jun, LIANG Jia-qi, SUN Jia-heng, WANG Ke-shu
    2019, 26(12):  2176-2180. 
    Asbtract ( )  
    Related Articles | Metrics
    The model of sugar precipitation of traditional Chinese medicine is established, and the crystal size distribution is not considered. Based on Lyapunov’s theory, an adaptive robust control for uncertain nonlinear system is proposed. The algorithm is based on “model decomposition” that adaptive controller eliminates the parameter uncertainties, robust controller eliminates the unknown dynamics and disturbance and feedback controller dominates the nominal object. These three controllers constitute a complete controller for the uncertain nonlinear system. The stability of the system is proved and the output of the system can well track the expectation. The algorithm is applied to the control of sugar precipitation in traditional Chinese medicine solution, and the simulation results verify the validity of the proposed algorithm.

    Multi-model Soft Sensor Modeling Based on the DP-RFR Method

    2020, 27(1):  64-69. 
    Asbtract ( )  
    Related Articles | Metrics
     A practical industrial process is often a large-scale complex system with muti-operating modes and nonlinearities, making it difficult to fully mine the data information through a single soft sensor model. To solve this problem, a multi-model soft sensor development approach based on the density peak (DP) clustering and the random forest regression (RFR) is proposed to estimate dominant variables. Firstly, classify the training data by means of the DP clustering algorithm; secondly, establish regression sub-models based on the samples of each category by using the RFR method; finally, apply the switching method for multi-model fusion. The proposed method has been utilized to develop soft sensors of the Tennessee Eastman process and the butane distillation process for estimating the contents of G and propane, respectively. The simulation results illustrate that the estimation accuracy has been improved, which can verify the effectiveness of the proposed method.

    A Two-person Interaction Recognition Algorithm Based on Active Curve Model

    WANG Pei-yao, CAO Jiang-tao, JI Xiao-fei
    2019, 26(2):  241-245. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to solve the issues in the two-person interaction recognition algorithm, such as the high dimension of the feature and weak representation ability, a novel algorithm based on the active curve model is proposed in this paper. Due to the advantage of the active curve to the sparse representation ability of the targets, the proposed algorithm obtains the deformable templates of the active curve by utilizing Gabor filter and Sum-Max Maps, then gives the sparse representation of two-person interaction. In addition, the proposed algorithm uses HOG features to describe all frames in the video sequences, then innovatively uses the distance of the extreme value method to get key frames of video sequences. Finally, the performance of the proposed algorithm is tested on the UT-Interaction dataset. The experimental results show that the active curve model extracted in the key frames is simple and has better representation ability, which obtains better interaction recognition rate. So the sparse representation of the algorithm in the field of interaction recognition has good research prospect.
    Decoupled Nonsingular Fast Terminal Sliding Mode Control Based on Super Twisted Algorithm
    TU Yu, WANG Yi, WU Zhi-hai, LUO Fei
    2020, 27(02):  271-277. 
    Asbtract ( )  
    Related Articles | Metrics
    A novel super twisted decoupling nonsingular fast terminal sliding mode control (STDNFTSMC) method is proposed for the existence of singular phenomena and sliding mode jitter in a class of four order under actuated system decoupling terminal sliding mode control. The under actuated system is divided into two subsystems, and nonsingular fast terminal sliding mode surfaces are designed, respectively. The saturation function of sliding surface of one subsystem is used to construct an intermediate variable, and the variable is introduced into the sliding surface of another subsystem to construct the sliding surface of the whole system. Equivalent control method and super-twisted reaching law are used to solve the control law of the system. The chattering phenomenon is effectively eliminated and the robustness of the system is improved. The Lyapunov method is used to prove the asymptotic stability of the sliding surface of each system. The simulation results show the effectiveness of the method.
    Nonlinear Iterative Predictive Control Based on RBF Neural Network
    JIANG Xue-ying, TAO Wen-hua, SHI Hui-yuan, SU Cheng-li, GUO Ying
    2019, 26(3):  454-460. 
    Asbtract ( )  
    Related Articles | Metrics
    For the controlled object with the complex and strong nonlinearity in the industrial process, a nonlinear iterative predictive control based on RBF neural network is proposed. This algorithm adopts the RBF neural network to approximate the nonlinear system, which is used as the predictive model. Meanwhile, in order to avoid missing some information of the system in each sampling time with respect to linearization, the internal predictive output along the future trajectory is expanded using the methods of Taylor series expansion and the internal iteration. Therefore, the solution of the complex nonlinear optimization is transformed into an easy quadratic programming and it can overcome the difficulty of online real-time computation of the nonlinear equation. Finally, the predictive control law is directly derived. The simulation comparison results for the CSTR process show that this algorithm has a good ability of tracking and disturbance rejection.
    The Research on Oil Separation System Performance Evaluation
    QU Bo, ZHAO Hong-ye, GAO Xiang, JIANG Bi-bo, ZHAO Deng-quan
    2019, 26(4):  670-674. 
    Asbtract ( )  
    Related Articles | Metrics
    The control system as offshore oil platform connecting the core of the control aspects of the production.And PID controller as an important part of the control loop control system, often due to changes in working conditions and other causes varying parameters mutation occurs in the system and cause its performance may be degraded. In this paper, reliability of PID controller performance evaluation method based on minimum variance control for the PID controller. Construction of Offshore oil and gas separation system simulation test model with semi-physical simulation technology, and use this model to simulate offshore oil and gas separation process simulation study of the control system. Multi-bus technology to ensure communication with the computer simulation model, simulation system platform to achieve real-time monitoring parameters. Finally, the test results show that the model simulation of real-time evaluation PID algorithm can effectively improve the performance of the control system.
    Stabilizable Region for Markov Jump Systems with Gaussian Transition Probability
    ZHOU Zi-heng, LUAN Xiao-li, LIU Fei
    2019, 26(5):  859-863. 
    Asbtract ( )  
    Related Articles | Metrics
    For discrete-time Markov jump linear systems with truncated Gaussian transition probabilities (GTP), the mean and the variance of GTP based state feedback controller and stabilizable region are investigated in this paper. To reduce the conservativeness of the existing results, we introduce the mean and the variance of TGTP into the design of the controller. Furthermore, to reveal the essential influence of system parameters, the mean and the variance of TGTP on controller design, the explicit solution of stabilizable domain is derived based on the approach of matrix eigenvalues boundary. Finally, several examples are presented to demonstrate the effectiveness of the proposed method.
    T-S Fuzzy Identification Method Based on Nearest Neighbor Fuzzy Clustering
    WANG Na, HU Chao-fang
    2019, 26(6):  1068-1073. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the identification accuracy of the T-S fuzzy model, and to solve the problem of determining the clustering centers in the traditional clustering algorithms, a Nearest Neighbor Fuzzy Clustering-based (NNFC) T-S fuzzy identification method is proposed. Firstly, the proposed nearest neighbor clustering approach decreases the subjectivity of the artificial presetting for the initial parameters of clustering. And the computation efficiency of clustering is also increased. Furthermore, the result of nearest clustering is afforded for the initial parameters of the Fuzzy c-Means (FCM) algorithm. Thus the premise parameters in the fuzzy rules are identified accurately. Finally, the Stable Kalman Filter (SKF) method is combined with the presented NNFC to estimate the consequent parameters quickly. The effectiveness of proposed method is verified by the classic chemical pH neural process. 
    Research on Optimal Scheduling Strategy of Generalized Power Sources in Active Distribution Network
    LI Ying, ZHAO Feng, WU Meng-di, WEI Li-bing
    2019, 26(7):  1291-1297. 
    Asbtract ( )  
    Related Articles | Metrics
    System power loss and voltage deviation of the active distribution network have important influence on the system operation safety. Firstly the influence of generalized power sources output on active distribution network is considered in this paper, the outputs of generalized power sources are taken as control variables to obtain the multi-objective optimization model with both minimum of the system power loss and node voltage deviation in active distribution network as the objective function. Secondly the model of multi-objective function is transformed into a single objective function by using the fusion of AHP and the entropy method, and then the active power output values of generalized power source are optimized with the chaotic particle swarm optimization algorithm. Finally the feasibility and superiority of the proposed model and algorithm are verified with both the improved IEEE-33 nodes system and a practical active distribution network system respectively as examples.

    Parameter Estimating of Asynchronous Motor Based on Variable Frequency Excitation Response Test

    LUO Jin-sheng
    2019, 26(8):  1521-1525. 
    Asbtract ( )  
    Related Articles | Metrics
     In order to improve the image segmentation accuracy, and solve the problems in the traditional fuzzy For the issue that the parameter estimation of squirrel cage induction motor, a parameter estimation method based on the variable frequency excitation response test is proposed. First, when the rotor is at rest, a variable-frequency excitation signal with the frequency range 0.5 Hz to 150 Hz is applied to the two phases of motor through an AC voltage source. Then, the frequency response of the motor to these signals is measured, so as to estimates the resistance and inductance parameters of the motor single-cage and double-cage models. The actual speed and torque of the motor are measured by experiments, and the results are compared with the calculated speed and torque based on estimated parameters. The results show the effectiveness of the method.
    Study for Flexible Flow Shop Scheduling Problem with Advanced HNN Algorithm#br#
    #br#
    LIN Shuo, CHEN Shi-jia, HAN Zhong-hua
    2019, 26(9):  1667. 
    Asbtract ( )  
    Related Articles | Metrics
     In order to solve the flexible flow shop production scheduling optimization problem (flexible flow shop schedule problem FFSP), this paper proposes a Hopfield neural network algorithm based on the principle of simulated annealing as a global optimization algorithm. This algorithm puts forward the permutation matrix of FFSP problem, and gives the energy function expression of FFSP problem, and to overcome the standard hopfield neural network algorithm (hopfield neural networks HNN) in solving FFSP easy to fall into local minimum solution of defects, the simulated annealing algorithm is applied to the hopfield neural network to solve, ensure that the output can be dispatched when the energy function tends to be stable. Finally, the advanced HNN algorithm is tested by using examples of different scales, the advanced HNN algorithm is compared with the traditional genetic algorithm and compact genetic algorithm the experiment results show that the advanced HNN algorithm is an effective method of solving FFSP problem.
    Adaptive Fault Estimation and Fault-Tolerant Control of a Flexible Hypersonic Vehicle
    HUANG Xin, WANG Jie, MA Xiao
    2019, 26(10):  1850-1856. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the security and reliable of the hypersonic vehicle, an adaptive sliding mode fault-tolerant control method is proposed to deal with the actuator faults. Firstly, a fault model is established based on the longitudinal dynamic model of flexible hypersonic vehicles, and transformed into strict feedback form. Secondly, the Back-stepping method is utilized to design the control input, and the adaptive sliding mode fault tolerant control law is proposed to deal with the actuator faults timely and quickly. Finally, the stability of the system is proved by Lyapunov stability theory. Simulations results show that the proposed method can effectively deal with the actuator effectiveness loss fault, and has good robustness and fault tolerant performance.
    Nonlinear Integral Sliding Mode Control Method Based on New Reaching Law
    LI Tao-chang
    2019, 26(11):  2031-2035. 
    Asbtract ( )  
    Related Articles | Metrics
    A nonlinear integral sliding mode control method based on a new reaching law is proposed for a class of nonlinear systems with uncertainty. First, a kind of nonlinear integral sliding mode surface was designed and good performance during the sliding mode stage was ensured. Second, a new fast reaching law was constructed and the finite-time reachability property of the reaching law was verified. And then, a sliding mode controller was designed based on the proposed nonlinear integral sliding mode surface and the reaching law. The stability bound of the closed-loop sliding mode control system with bounded disturbances was derived. Finally, the effectiveness and superiority of the proposed method was verified by a series of simulation experiments.

    Ventilation System Design of Urban Utility Tunnel Based on Fuzzy PID Control Algorithm

    YAN Hui, YAN Yong-feng, LU Rong-xiu
    2019, 26(12):  2181-2187. 
    Asbtract ( )  
    Related Articles | Metrics
    The ventilation system of urban utility tunnel is the key to ensure the safe operation of tunnel. As  the ventilation system with high noise, multivariable, nonlinear and time-varying delay, a fuzzy PID control algorithm is em-ployed to upgrade ventilation system performance. First, the Kalman filter and multi-sensor information fusion technology are applied to process the collected data. Then, the fuzzy parameter self-tuning control algorithm is adopted to adjust the parameters of PID to achieve the intelligent control for air volume. The simulation results show that the response speed, steady state accuracy and overshoot of the control algorithm are much better than the conventional PID control, which provides a reliable guarantee for safety, stable and efficient operation of urban utility tunnel.
    Three Dimensional Geometric Dynamic Modeling of Hazardous Chemicals Storage Based on Image
    DAI Bo, LI Yan-fei, AN Hai-yang, ZHOU Ze-yu, LIU Xue-jun
    2020, 27(1):  70-76. 
    Asbtract ( )  
    Related Articles | Metrics
    Safety production supervision departments have strict regulations for the five-distance of the hazardous chemicals storage warehouse stacks (distance, pile wall distance, zenith distance, spacing and channel spacing), the dynamic supervision requirements can be achieved by describing the changes of the position of the stacks in the warehouse through the three-dimensional dynamic geometric modeling. Three-dimensional geometric dynamic modeling of the stacks based on image is proposed. In order to establish the corresponding relations between image points and objects, a five - element imaging model is constructed and two - point calibration method is proposed. On the basis of calibrating the parameters, the solution space of the coordinates of the point is obtained first, and then the real solution space is obtained by combining the constraint condition to realize the static  three - dimensional geometric reconstruction of the stacks. Then, the stacks are identified and reconstructed in the image sequences, and the dynamic geometric modeling is realized.

    Detection of Construction Vehicles Under the Transmission Corridor in UAV Inspection

    WU Jin-ting, ZHAO Xiao-guang, YUAN De-cai
    2019, 26(2):  246-250. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to solve the problem of construction vehicles under the transmission corridor in UAV inspection, an automatic detection algorithm for construction vehicles based on image processing and machine learning is proposed. First of all, the image collected by the UAV is preprocessed; secondly, according to the color and linear structure features of construction vehicles, two extraction methods of construction vehicles are given, effectively narrowing the range of recognition; finally, this paper chooses the method based on HOG feature and support vector machine (SVM), and gives a construction vehicle identification method. The experimental results show that the proposed algorithm can detect the presence of construction vehicles in complex scenes under the transmission corridor, and has good accuracy.
    Infinite Time Horizon H2/H∞ Control for Delayed Nonlinear Stochastic Systems
    ZHU Huai-nian, LI Fang-chao, ZHANG Cheng-ke
    2020, 27(02):  278-287. 
    Asbtract ( )  
    Related Articles | Metrics
    This paper investigates the problem of H2/H∞ control for nonlinear time-delay stochastic systems with state, control, and disturbance–dependent noise. Firstly, a sufficient condition for the existence of the nonlinear stochastic H2/H∞ control with time-delay is presented in terms of coupled Hamilton–Jacobi equations (HJEs). Secondly, by using the T-S fuzzy model, the stochastic H2/H∞ controller can be designed via solving a set of linear matrix inequalities (LMIs) instead of coupled HJEs. Finally, a numerical example is employed to show the effectiveness of the results obtained.
    Optimal PID Control Based on the Improved Dynamic Mutation Differential Evolution Algorithm
    TAN Fei, CAO Li-jia
    2019, 26(3):  461-468. 
    Asbtract ( )  
    Related Articles | Metrics
     In order to improve the speed and accuracy of PID control parameter optimization and guarantee the global optimum solution, an improved dynamic mutation differential evolution (DMDE) algorithm is proposed. The DMDE algorithm employs the random mutation and dynamic population, and increases the learning probability of the elite individual, to improve the speed and accuracy of optimization. Furthermore, the DMDE algorithm is used to find out the optimum solution of PID control for five types of common industrial plant models under seven types of integral performance indices of errors. The results of simulations and sensitivity analysis of the optimal control system indicate that the DMDE algorithm has better performance than the normal DE algorithm, and is more suitable to evaluate the system stability and speediness by the criterions of integrated time absolute error (ITAE), integrated root absolute error (IRAE) and developed integrated time absolute error (DITAE).
    Traffic Control with Bus Priority Based on Cooperative Chaos PSO Algorithm
    CAI Yan-guang, HUANG Bai-liang, CAO Hao, HUANG He-lie, QI Yuan-hang
    2019, 26(4):  675-681. 
    Asbtract ( )  
    Related Articles | Metrics
    Focusing on the problem of cooperative control of public transport priority in multi-intersection of the regional road network, this paper proposes a degraded modeling strategy and establishes a multi-intersection traffic signal collaborative optimal control model for the goal of minimizing passenger per-capita delay based on the strategy. By introducing the chaos optimization strategy and multi-group cooperative search strategy, this paper presents a multi-group cooperative chaotic particle swarm optimization algorithm for solving the model. The experiments show that the proposed model and algorithm have good practicability. Compared with the Webster fixed timing scheme, the genetic algorithm and the standard particle swarm algorithm, the proposed algorithm can get better signal timing scheme which can effectively reduce the per-capita delay.
    Research of Fault Location Based on FTU for Closed Distribution Network
    HU Fu-nian, ZHANG Ren, GE Miao-miao
    2019, 26(5):  864-871. 
    Asbtract ( )  
    Related Articles | Metrics
     In order to solve the problem of accurate fault location of single-phase ground fault in the closed distribution network with multiple power and cross branch, the fault location method based on the information from the multi-terminal FTU that is adjacent to the fault branch is proposed. The method is based on the theory of graph theory to form the fault information matrix of the distribution network topology that gets the fault criterion of the cross branch to solve the problem of false judgement in fault location. The fault section can be quickly and accurately determined in the complex network. According to the circuit characteristics of the directed graph topological structure of the ground loop of both ends of power, the effect of the grounding resistance at fault point on fault location can be neutralized, therefore the accuracy of fault location would be improved. This method takes full advantage of the existing FTU equipment, so there is no need to increase additional equipment investment, additionally, it can eliminate the error caused by other introduced links and be applied to complex distribution network. The proposed method is simulated by 11 node distribution network, and the validity and accuracy of the method are verified. 
    EEG De-noising Method Based on Nolinear Multiscale Representation
    GENG Xue-qing, SHE Qing-shan, ZHANG Qi-zhong, MA Yu-liang
    2019, 26(6):  1074-1080. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to extract meaningful information from noise-contaminated Electroencephalogram (EEG) signals with the characteristics of non-stationarity, non-linearity and low signal-to-noise ratio (SNR), a new EEG de-noising method is proposed based on nonlinear multiscale representation in this paper. First, the singularity locations of EEG signal are detected. Secondly, EEG signal is processed by the nonlinear mulitscale representation (NMR) algorithm which uses nonlinear prediction operator constructed by polynomial cell-average interpolation in the vicinity of the intervals containing singularities while adopts linear prediction operator in other intervals. Next, the de-noised signal is obtained by reconstructing transform coefficients which are processed by threshold value at each scale．The efficiency of the proposed approach has been demonstrated by comparison with Garrote threshold, wavelet transform using hard threshold, soft threshold and adaptive threshold on both synthetic data and real BCI Competition IV Data Set 1. Experimental results show that this algorithm has a certain practicality and can be used to eliminate the noise of EEG signal in the brain-computer interface (BCI) system.
    Research on Optimal Vehicle Scheduling in Open Mine Under Uncertainty 
    ZHOU Tian-pei , YANG Li-juan , SUN Wei
    2019, 26(7):  1298. 
    Asbtract ( )  
    Related Articles | Metrics
    In view of the present situation that research on optimal vehicle scheduling in open mine under uncertainty is less, the optimization objective function and constrains of vehicle scheduling are discussed firstly, and then the stochastic expected value goal programming model is established. In the process of solving the model, the chaotic theory is applied because of local convergence of PSO algorithm, and adaptive chaotic PSO algorithm is proposed. The proposed algorithm is applied to the vehicle scheduling in an open mine, which can enhances the global convergence effectively compared with the traditional PSO algorithm.
    Three-link Robot Control System Design based on Parametric Solutions
    GU Da-ke, TANG Chong-jian
    2019, 26(8):  1566-1571. 
    Asbtract ( )  
    Related Articles | Metrics
    For the three-link robot controller design problem, the control law based on link rotation angle and angular velocity is proposed and solved the problem of three-link robot control. Firstly, with the proposed controller parametrization, the three-link robot system, though nonlinear, can be turned into a constant linear system with desire eigenstructure. Secondly, in such a design there are still degrees of freedom which may be further utilized to improve the system performance. Finally, a direct parametric algorithm is proposed and the validity of the algorithm is verified by Simulink. And the simulation results show that the three-link robot is supposed to arrive the UEP (upright equilibrium point) steady by the function of the controller.
    Anti-saturation Robust Stability and   Performance Analysis for Networked Control Systems
    PENG Gao-feng, LIU Gang, LENG Yang, TAO Neng-ru, ZHAO Na
    2019, 26(9):  1675-1681. 
    Asbtract ( )  
    Related Articles | Metrics
    For a class of network control systems(NCSs) with actuator saturation and time-varying delay, anti-saturation robust stability and  performance are studied under the unequal interval sampling in this paper. First of all, for the NCSs with actuator saturation, a saturation controller is designed, and a mathematic model is established. Based on the analysis and processing of the sampling interval and time- varying delay, the discrete mathematics model of the closed-loop systems is established. By using a method of processing the uncertain terms, the system states are expressed in other uncertain terms of the NCSs. Then, by constructing the Lyapunov function, using the   control method and the linear processing method, a delay-independent stability criterion based on LMI description systems for NCSs is obtained. Finally, the validity of this conclusion is illustrated by comparing with some methods of other literature for upper bound of time delay under different  norm bound.
    Research on Control Algorithm of Two-Inertia Resonance System
    PAN Heng
    2019, 26(10):  1857-1862. 
    Asbtract ( )  
    Related Articles | Metrics
    Since two-inertia resonant system is inclined to produce low frequency mechanical resonance, the two degree of freedom speed controller with feed forward & feedback control and the full state feedback controller are proposed to solve the problem. Based on the kinetic equation of the motor and the load, the mathematical model of the two-inertia resonance system is established. And the two degree of freedom controller and the state feedback controller are designed based on this model. Considering the reference input tracking ability and the anti-disturbance torque capability of the control system, the gain of the control system is obtained by different pole allocation strategies. Contrast simulation results show that the proposed speed control algorithm is feasible and effective.

    Method of Dynamic Positioning State Estimation Based on MCMC Particle Filter

    YANG Yi-fei, BAO Wei-er
    2019, 26(11):  2036-2040. 
    Asbtract ( )  
    Related Articles | Metrics
     State estimation is an important part of the control part of the dynamic positioning system. In order to keep the ship in the target position, the accurate ship status information is needed. In view of the strong nonlinear problems such as extended Kalman filter and unscented Kalman filter, which are filtered by Gauss approximation and cannot adapt to ship motion, an improved particle filter algorithm based on Bayesian estimation is adopted. In order to reduce the degeneracy and impoverishment of standard particle filtering, MCMC(Markov Chain Monte Carlo) is introduced to construct Markov chains to produce samples from target distribution, and to reduce the correlation between particles. The simulation results show that the improved particle filter can separate the low-frequency motion information from the measurement information containing high-frequency motion information and noise. The filtering accuracy is higher and the stability is better.

    Arc Length Control of Welding Machine Based on Variable Universe Fuzzy PID

    MAO Jun, LIU Si-yang
    2019, 26(12):  2188-2192. 
    Asbtract ( )  
    Related Articles | Metrics
    Considering that in the research of current brazing technology, most of the adjustment of arc length needs manual operation, so it is impossible to control the arc length accurately. However, the control method of the existing automatic control system is relatively backward, and the response characteristics and stability are poor. The control method of welding gun manipulator of brazing equipment is studied in this paper, and a welding machine arc length adjusting control method based on variable domain fuzzy PID is studied. Through numerical simulation and experiment, it is verified that the arc length adjusting control method based on variable universe fuzzy PID has short adjusting time and almost no overshoot. Using this method to adjust the arc length under various working conditions is conducive to maintaining the arc stability.
    Improved VSG Control Method Based on Impedance Identification for Reactive Power Sharing in Parallel Inverter System
    YANG Cai-ming, SUN Li-jing , WU Ming, YU Jie, TAO Hong-fei, LUO Gang, ZHANG Li-zong
    2020, 27(1):  77-83. 
    Asbtract ( )  
    Related Articles | Metrics
    As an effective supplement for smart energy in Internet, Microgrid (MG) could realize the frequency and voltage supporting functions and allocate the load power automatically when it runs in the island mode. As the Virtual Synchronous Generator (VSG) control with drooping feature can realize the automatic power distribution of the inverter according to the design parameters due to its inertia and damping links. However, due to the differences and changes in the impedance of the inverter connection lines in the microgrid, the VSG cannot only rely on the designed droop parameters to achieve the sharing of reactive power in full work conditions. Therefore, an improved reactive-voltage control method of VSG based on short-time pulse injection line impedance identification is proposed. The line voltage drop generated by each inverter is compensated by identifying the line impedance in advance, and a parallel inverter is realized common bus voltage-reactive droop control to compensate for the impact of line impedance voltage drop on the rational distribution of reactive power. The principle and implementation of the improved reactive power control under the control of VSG are analyzed, and the effectiveness of the method is verified by some simulations.

    Multi-objective Particle Swarm Optimization with Black Hole Mechanism and Chaotic Search

    XIA Yu, WU Peng
    2019, 26(2):  251-257. 
    Asbtract ( )  
    Related Articles | Metrics
    MOPSO is easy to fall into local optimum in the late stage of the algorithm, in order to prevent the "premature", the multi objective particle swarm optimization algorithm with black hole mechanism and chaotic search is proposed. The random black hole mechanism is adopted to search around the lead particle. By characteristics of chaos ergodicity, the search area around individual optimal point has expanded, so as to increase the diversity of the population and prevent falling into local optimum. The solution of improved ZDT series functions show that the algorithm can solve the problem of high dimensional solutions in 2-dimensional space, and the solution of the improved DTLZ series functions show that the algorithm can effectively solve the 3-dimensional space.
    Discrete Wolf Pack Algorithm for Permutation Flow shop Scheduling Problem
    XIE Rui-qiang, ZHANG Hui-zhen
    2020, 27(02):  288-296. 
    Asbtract ( )  
    Related Articles | Metrics
    A discrete wolf pack algorithm is proposed to simulate the specific characteristics of the permutation flow shop scheduling problem and simulate the hunting behavior of wolves in nature. Using the coding method based on the workpiece sequence, the opposition learning initializes the population to improve the convergence speed of the algorithm. The redesign of the wandering behavior, summoning behavior and siege behavior in the original wolf group algorithm makes the algorithm not easy to fall into local optimum. At the same time, the Taguchi experimental design method is used to analyze the sensitivity of the algorithm parameter settings, and the optimal parameter combination is determined. Finally, the discrete wolf pack algorithm is used to simulate and test the standard test sets of Car, Reeves and Taillard. Compared with other intelligent optimization algorithms, the feasibility of the proposed algorithm is verified. It provides a more effective method for solving the permutation flow shop scheduling problem.
    Tracking Endpoints of Indoor Structure Lines Based on the Backprobing Optical Flow Algorithm
    ZENG Bin, WANG Heng-sheng, PENG Tian-bo
    2019, 26(3):  469-475. 
    Asbtract ( )  
    Related Articles | Metrics
    Tracking features on image time series have huge potential for many applications, but the popular optical flow tracking algorithm is less practical because of its less accuracy. To tackle this problem, this paper proposes a method of tracking endpoints of indoor structure lines based on backprobing of optical flow. The endpoints of the building structure lines indoor are used as target features to be detected on the reference frame of image series, then the features are tracked using the optical flow algorithm to obtain the corresponding positions on the next frame of images; The idea is backprobing which means tracking the corresponding positions back to the reference frame to get the backprobing positions, and comparison is made between the original feature positions and the backprobing positions which should be no difference ideally on the reference frame; The effective features are finally selected by eliminating the ones with large differences. This improved optical flow tracking algorithm is applied to the visual odometry, and the experiment results show that the image features of structure-line-endpoints are stable, and the backprobing optical flow tracking method has a high accuracy, and the final trajectory of the visual odometry is significantly improved compared with the traditional optical flow algorithm.
    Research on Dynamic Prediction Method of Civil Aircraft Fuel Consumption
    ZHANG Jun, YANG Gui-bin, PENG Xiao-feng, MU Xiao-yan
    2019, 26(4):  682-687. 
    Asbtract ( )  
    Related Articles | Metrics
    A fuel consumption prediction method with the characteristics of aircraft age based on actual civil aircraft is presented. Through the analysis of the fuel consumption of aircraft operations at different stages, a dynamic prediction method is proposed based on the least squares support vector machine (LSSVM), and an improved particle swarm optimization method is proposed to optimize the LSSVM parameters (IPSO-LSSVM); In order to increase the prediction accuracy, a two-dimensional prediction model based on horizontal and vertical is put forward to make the fuel consumption prediction of aircraft operation more consistent with the actual situation. Finally, the effectiveness of the proposed method is validated by the practical data of aircraft operation, furthermore, the proposed method has better estimating performance than the traditional LSSVM method.
    Optimized Sliding Mode Control of Power Plant SCR  Flue Gas Denitration System#br#
    #br#
    2019, 26(5):  872-878. 
    Asbtract ( )  
    Related Articles | Metrics
    Along with the consciousness of environment protection increased, the limitation of allowed emission of nitrogen oxide from power plant becomes more and more rigorous. Study the model of SCR flue gas denitration system as the controlled plant, the design that the limitation of amplitude and changing rate of control variable is used as feed-forward compensation is proposed; using differential evolution algorithm to bring the ability of adaptive to the designed sliding mode control system by the help of the designed auxiliary sliding surface. Based on the proposals mentioned above, the offset free adaptive optimized sliding mode control by using cascaded differential evolution algorithm is presented. The simulation results indicate that the optimized control systems gave above could reach the control requirement of SCR flue gas denitration system, their control quality and robustness are better than traditional way, and the practical significance is proved.
    Research on Robot System for Information Detection of Bipolar Coal Mine #br# Disaster#br#
    #br#
    WANG Tai-hua , ZHANG Le-yi , QIN Yu-xin
    2019, 26(6):  1081-1084. 
    Asbtract ( )  
    Related Articles | Metrics
    Based on the coal mine actual characteristics, a robot system of coal mine disaster information exploration is designed in this paper. This robot walks along the I-beam track of the coal mine and uses the wireless control. When the disaster happens, the robot runs as quickly as possible to the nearest place of disaster, it can get the image and the information of the disaster environmental. And the information obtained is transmitted to the ground command center in real time. The system reaches a preliminary design requirement through the actual test.
    Research of Sine Signal Amplitude and Phase Property's Measurement Based on Interactive Learning
    Sine signal, iterative learning, amplitude and phase property
    2019, 26(7):  1304-1307. 
    Asbtract ( )  
    Related Articles | Metrics
     In actual industrial applications, many measurement problems are essentially the corresponding sine signal amplitude and phase characteristics' measurement. For the sine signal with DC offset, measurement noise and frequency change, an amplitude and phase's measurement method based on iterative learning is proposed. Firstly, the parameters which need to be measured should be estimated one step. The iterative learning law should be set as the derivatives of the difference's square of measurement output value and estimation output value, and the parameters. The estimation algorithm is established when the derivatives are weighted properly. Simulation results show that when the measurement error's variance is at the level of the tenth of the maximum measured value, each measured parameter's estimated error can be up to one percent or smaller. Moreover, with a decrease of noise level, each parameter's estimated accuracy increase rapidly. This method can achieve high-precision measurement of sine signal's amplitude, phase, frequency and DC offset, and it also has great prospect for interferometer's electronic subdivision and motor's displacement measurement based on magnetic field information.
    Neural Network Identification on Hydraulic Position Driving Unit 
    HAN Gui-hua, ZHAO Yu-xiu, SHI Yu-chun, LIU Jia-chun
    2019, 26(8):  1454-1459. 
    Asbtract ( )  
    Related Articles | Metrics
    The Elman network are used to identify model of the quadruped robot hydraulic driving position unit since the mathematical model of linear differential equations that can not represent the actual system. In order to reduce the error between Elman network output and expected output, BFGS and GDX are used to correct the weight of the network and Mean Square Error (MSE) and Normalized Mean Square Error (NMSE) are used to correct the error function. BP neural network is designed in order to on-line adjust PID parameters based on identification model. The experimental results show that the fitting accuracy between the identification model data and the experimental data is high, and the BP neural network PID algorithm based on the identification model is effective, which further verifies the validity of the identification model.
    Study on Fault Diagnosis of Rolling Bearing Based on MFCC and CDET
    WANG Qian, WANG Gang, JIANG Han-han, CHEN Shang-qing
    2019, 26(9):  1682-1686. 
    Asbtract ( )  
    Related Articles | Metrics
    Aimed at the problem that the vibration sensor is difficult to be installed in engineering application and the feature vector is redundancy, a method of fault diagnosis for rolling bearing based on MFCC and CDET is proposed. The noise signal is used for monitoring the condition of rolling bearing when the machine is running. MFCC features are extracted from the noise signal and CDET is employed to reduce the dimensionality of MFCC features. Finally, the features after feature reduction are used as the inputs of SVM classifier for fault classification and its performance of feature reduction is compared with PCA. The experimental result shows that CDET has better performance of feature reduction in noise diagnosis and the method based on MFCC and CDET can detect the fault category accurately and effectively.
    Routing Control of Multi Commodity Flow Vehicles for Virtual Vehicle Communication Network
    GUO Xu-kun, FAN Bing-bing, CHEN Chun-lian, SUN Gang
    2019, 26(10):  1863-1869. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the traffic efficiency of vehicles in traffic road network, a multi commodity flow back pressure routing control strategy based on virtual vehicle communication network data is proposed. Firstly, the road network composed of on-board wireless network nodes was used for the implementation of the road and vehicle information collection. In order to improve the real-time and forward-looking routing control, here introduce traffic flow forecasting methods to construct the virtual vehicle queue. And then the multi commodity flow backpressure routing method was put forward, and vehicle adaptive routing control strategy was designed. According to the status of traffic pressure, the improvement on the back pressure strategy weight is realized, which could enhance the ability to adapt to backpressure routing algorithm parameter optimization. Finally, simulation experiments show that the proposed method can be more effective in traffic vehicles controlling and the traffic smoothness can be improved.

    Status and Prospect of Earth Pressure Balance Control Modeling for Shield’s

    Sealed Cabin

    XU Sheng, LIU Xuan-yu, HUANG Yue-yang
    2019, 26(11):  2041-2046. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to achieve the automation and intellectualization of shield tunneling process and to ensure the safety of construction, it is necessary to build an effective pressure control model of sealed cabin, which is one of the hottest and the most difficult problems in shield technology. Firstly, the research status of sealed cabin’s pressure control model of shield was described from two aspects of mechanism modeling and field data modeling, and the representative models were analyzed. Then, this paper summarized the problems that existed in model and needed to be solved urgently were summarized, such as modeling without considering the characteristics of time-lag, non-linear and time-varying of earth pressure balance system, which leaded to poor robustness and stability of model. Finally, the feasible methods of solving existing problems were proposed, and the prospect of future research on the control model of earth pressure in sealed cabin was given.

    Mechanical Spindle Vibration Prediction Model Based on RBF Network

    PIAN Jin-xiang, PU Chun-yu, QI Yuan-wei, WANG Zhan, ZHI Jie-feng
    2019, 26(12):  2193-2198. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to solve the existing problem of low accuracy and the difficulty of modeling in dynamic balance process modeling method of mechanical spindle rotor, a method of establishing mechanical spindle vibration prediction model using RBF network is proposed to realize the prediction of the spindle vibration amplitude under the different moving position of balance blocks. In the prediction model based on RBF network, DBSCAN clustering algorithm is introduced to determine the radial basis function centers in hidden layer of the network, so as to identify the hidden layer nodes objectively and improve the precision of the prediction model. Finally with the help of the dynamic balance test platform, the accuracy of the prediction model is verified, and the modeling method is compared with RBF network based on maximal matrix element method, RBF network based on K-means algorithm, BP network based on genetic algorithms and artificial neural network. The results show that the modeling method of mechanical spindle vibration prediction model proposed in this paper achieves effective prediction of the vibration amplitude with higher precision.
    Coordination and Optimization of Operation Time Conflict in Steelmaking and Continuous Casting
    LUO Xiao-chuan, SANG Mei-ning, DENG Meng-yi, FAN Yu-hao
    2020, 27(1):  84-91. 
    Asbtract ( )  
    Related Articles | Metrics
     In the steelmaking and continuous casting process, some disturbances can cause time clash. Dynamic scheduling and casting speed adjustment can be applied to eliminate it. Considering the two problems, mathematical model is set up. The object functions are the minimum time of the broken pouring, redundant waiting, drawing speed adjustment and the smallest acceleration adjustment. The constraint functions are based on the production process. The steelmaking and continuous casting operation process consists of continuous and discrete processes, the problem model is difficult to solve, this paper divides the problem into two parts: the time clash elimination model and the casting speed optimization model, and put forward the solving method for the two models. Through the method of solving the whole model, the dynamic scheduling and casting speed adjustment are applied to achieve the coordinative optimization of the two models.  

    Stabilizing Incremental Model Predictive Control and Its Applications in Contouring Control

    ZHANG Quan-peng, HE De-feng, WU Sai-nan, YU Shi-ming
    2019, 26(2):  258-263. 
    Asbtract ( )  
    Related Articles | Metrics
    This paper presents a stabilizing incremental model predictive control (MPC) algorithm for discrete-time multivariable linear systems with measurable disturbances. Taking the incremental state-space model as the predictive model, the finite horizon optimal control problem of MPC is formulated and the corresponding MPC controller is determined, which has a structure combining measurable disturbance feedforward with time-delay state feedback. Using the Lyapunov-Krasovskii stability theory of time-delay systems, we establish some sufficient conditions guaranteeing the stability of the closed-loop system with no constraints. Finally, the simulation example of a constrained biaxial contouring control system is employed to illustrate the validity of the algorithm proposed here.
    An Integrated Generation-consumption Dispatch Strategy with Wind Power and Photovoltaic
    LIU Xiao-rui, SU Yong-xin, TAN Mao, QIAO Hai-xiang
    2020, 27(02):  297-302. 
    Asbtract ( )  
    Related Articles | Metrics
    Wind power and photovoltaic output are uncertain. In view of the mismatched usable power and system natural load, an integrated dispatching system is put forward, which integrates the generation-side resources such as wind power, PV, thermal power and the demand-side resources such as electric vehicles and adjustable load. On the one hand, based on the fuzzy chance constrained programming model, the non-deterministic problems are equivalently rewritten for problem modeling and solving. On the other hand, considering the cost of electricity generation and consumption in the optimization objectives, the generation-side and demand-side interaction mechanism was applied in the constraints, so as to improve the supply-and-demand relationship between the renewable energy's output and load at a lower cost. Influences of the participation degrees of electric vehicles and demand response on the dispatching results were tested by digital simulation. The results show that the proposed method can not only match the load and output, but also effectively raise the economic efficiency.
    An Off-line Handwritten Chinese Character Cognitive Model Based on Simulated Feedback Mechanism
    WANG Jian-ping, WANG Guang-xin, LI Wei-tao, SONG Cheng-nan
    2019, 26(3):  476-483. 
    Asbtract ( )  
    Related Articles | Metrics
    For the drawbacks of existing cognitive models with same cognitive demanding and constant feature space constructed by DTCWT for various samples, an intelligent off-line handwritten Chinese character cognitive model with simulated feedback adjustment mechanism is explored in this paper, to simulate the human cognitive process of the adaptive adjusting feature space to repeat intercomparison and deliberately refine with various cognitive demanding. Firstly, an intelligent cognitive model with simulated feedback adjustment mechanism is proposed. Secondly, the cognitive demanding of samples is analyzed to establish the optimized DTCWT feature subspace and classified cognitive rules for various sample cognitive demanding. Thirdly, the evaluation criteria of cognitive results is defined to adaptively adjust the optimized feature subspace and classified cognitive rules based on the new cognitive demanding from the falsely cognitive samples. The optimized compact DTCWT feature space is established by integrating various optimized feature subspaces of multi-cognitive demanding. The experimental results based on GB2312-80 handwritten Chinese sample library show the superiority of our method.
    Multiple Model of Boiler NOx Emissions Based on Clustering and Weighted Connection
    ZHU Yu-Sen, JIN Xiao-Ming, ZHANG Quan-Ling
    2019, 26(4):  688-693. 
    Asbtract ( )  
    Related Articles | Metrics
    According to the characteristics of the boiler combustion process with nonlinear, multiple operating regions and multivariable coupling, a multiple-model modeling method based on fuzzy C means clustering and least squares support vector machines and weighted connections (FCM-LSSVM-WC) is proposed. The influence of inputs on outputs is employed to evaluate the difference between the samples. A BP neural network with "limited" processing is used to calculate the MIV. The membership weights are the MIVs which are used to realize classification and connect the multiple model. The proposed method is verified by taking the circulating fluidized bed boiler on a thermal power plant. Industrial applications show that compared with PLS, LSSVM, FCM-LSSVM, AP-LSSVM, the modeling method can ensure the generalization accuracy requirements, simultaneously possess better tracking ability in predicting NOx emissions of the boiler combustion process.
    Diagnosis of Control Loops Oscillations Based on EMD and Closed-Loop Testing#br#
    #br#
    KONG Jie, TIAN Xue-min, SHANG Lin-yuan
    2019, 26(5):  879-891. 
    Asbtract ( )  
    Related Articles | Metrics
    In this work, an algorithm combining Empirical Mode Decomposition (EMD) with closed-loop testing principle is presented for identification of multiple root causes for oscillations in closed-loop systems. EMD is used to decompose the controller output data and the system output data into a finite set of IMFs, and then the closed-loop testing principle can exactly isolate the source of oscillation corresponding oscillatory IMF by injecting extra testing signal. The improved approach is used for determination of multiple causes for oscillation in linear SISO systems. Finally, the simulation experiment on the continuous stirring and mixing process validates the effectiveness and reliability of the proposed method.
    Short-Term Load Forecasting Method Based on FFT Optimized Resnet Model
    XU Yan-lu, LU Yue, ZHU Bing, WANG Bin-bin, DENG Zhuo-fu, WAN Zheng-wei
    2019, 26(6):  1085-1090. 
    Asbtract ( )  
    Related Articles | Metrics
    Power industry requires accurate short-term load forecasting to provide precise load requirements for power system control and scheduling. In order to improve the accuracy of short-term power load forecasting, a method based on FFT optimized ResNet model is proposed. The model first defines power load forecasting as a time series problem, then introduces one-dimensional ResNet for power load regression prediction, and proposes to use FFT to optimize ResNet, the FFT transform of a layer of convolution results gives the model the ability to extract periodic features in the data. Experiments show that the prediction accuracy of FFT-ResNet is better than several benchmark models in 6-hour power load forecasting, which indicates that this method has a good application prospect in power load forecasting.

    Performance Evaluation of Bulk Cargo Port Based on GHS Functional Neural Network

    RAO Yi-fei, CHEN Dong-xu
    2019, 26(7):  1308-1314. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the effectiveness of the bulk cargo port productivity evaluation,a method based on Gauss harmony algorithm（GHS）and the improved functional link neural fuzzy network are combined to evluate bulk cargo port productivity. Firstly, according to the evaluation index of the operating properties, the comprehensive coverage of the model parameters is designed, and the selection of evaluation indicators of productivity bulk cargo port is realized by combining the actual property of data acquisition and process analysis; Secondly, the bulk port productivity evaluation model using the functional link neural network is designed, and the construction of bulk cargo port productivity evaluation model is realized by taking the network as the output of the network for model design of fuzzy rules; Finally, through simulation experiments, the fitting degree between the actual and expected outputs of the model is very close, which can achieve more than 95% sample data recognition efficiency, and can meet the accuracy requirement of bulk cargo port productivity evaluation in real bulk cargo port.
    Fault Peer Node Based Modeling Method for Non Cooperative Video on Demand
    ZHU Ming-xing, SUN Zheng-lai, LIU Wen-ye, WU Zhong-chao, XU Fei, YE Hai-feng, ZHAO Dai-ping
    2019, 26(8):  1526-1532. 
    Asbtract ( )  
    Related Articles | Metrics
     In order to further improve the accuracy of video on demand model for system behavior prediction, a method considering fault node based Model with non cooperative peer to peer assisted for video on demand is proposed. Firstly, the finite population representation model was constructed, which used the idle queue、the receiving queue and the failed queue as the components; Secondly, the peer to peer (p2p) network was used to describe the network behavior of video on demand system with three queue, and the numerical model of the system was also built, which gives the system state probability equation coefficient calculation process and system performance calculation formula; Finally, the experimental results show that comparing algorithms on the two indicators of uplink traffic utilization and service utilization is that the proposed method is superior to all selected, while the experimental part of the system is given a node failure performance of experiments.
    Aerodynamic Modeling and Control of Smart Wind Turbine Blades
    QI Liang-wen, CHEN Yan, HE Ke-shan, ZHENG Li-ming, ZHOU Qi, BAI Xing-zhi
    2019, 26(9):  1687-1694. 
    Asbtract ( )  
    Related Articles | Metrics
    Effective lift control of wind-turbine blades will reduce the fatigue loads of wind turbines, which can improve the reliability of wind turbines. This paper presents a simulation platform that contains a static lift control system of wind turbine blade test model with deformable trailing edge flap. In the system, the software, Matlab/Simulink, which serves as the host computer is used to establish the static lift mathematical model of the wind turbine blade test model and the system control algorithm. The real-time sampling and output are realized by PLC which serves as the slave computer. OPC technique is applied to realize the real-time communication between the host computer and the slave computer. The result shows that the control system effectively reduced the lift fluctuation of wind turbine blade test model under periodic gradient wind, periodic gust, choppy wind and the turbulent wind. Meanwhile, the control system can better make up for the lift fluctuation resulting from wind disturbance while using single neuron PID controller which has a better control result than using common PID controller.
    Multi-objective Combustion Optimization Based on Constrained Fuzzy Association Rule
    ZHENG Wei, WANG Chao, LIU Da
    2019, 26(10):  1870-1874. 
    Asbtract ( )  
    Related Articles | Metrics
    For improving boiler combustion performance of coal-fired power plant, a new optimized method based on constrained fuzzy association rule is proposed to determine boiler operation parameters. The associated relationship can be discovered between primary operation parameters and performance indexes by mining an ocean of historical operation data with different working conditions. According to the association relationship, the desired values of boiler parameters which are crucial to high-efficiency and low-emission operation can be acquired. Taking the data mining result of oxygen content in flue gas as an example, its optimization values in different working conditions are demonstrated. Multi-objective boiler combustion optimization based on constrained fuzzy association rule doesn’t only provide the theoretical basis for regulating boiler parameters at present, but also establishes the foundation on set points of important parameters for closed-loop control in the future.

    Soft Sensor for Intensive Aquaculture Process Based on GA-SVR

    LI Kang, WANG Wei, Lin Shao-han
    2019, 26(11):  2047-2051. 
    Asbtract ( )  
    Related Articles | Metrics
    As ammonia nitrogen concentration measurement in the intensive aquaculture process is difficult online, large investment and low precision, a soft sensor modeling method based on GA and SVR is proposed. Firstly, according to the analysis of aquiculture water quality influence factors, water temperature, dissolved oxygen, pH and conductivity are collected and used as auxiliary variables. Then, GA is used to optimize penalty parameter C and kernel function parameter g in SVR. Finally, the SVR model is used to predict the ammonia nitrogen concentration in water during aquaculture process. The predicted results were compared with BP, RBF neural network and SVR model based on grid search. The experimental results show that the soft-sensing method based on GA-SVR has better prediction accuracy, it can also provide effective operation guidance for the control and optimization of the intensive aquaculture process.

    The Improved Finite Control Set Model Predictive Control Method to the New Inverter

    LEI Xiao-ben, LI Xue-feng, WANG Chuan-qi, Han Jian-ding
    2019, 26(12):  2199-2204. 
    Asbtract ( )  
    Related Articles | Metrics
    To aim at the requirement of low total harmonic distortion (THD) in the aviation inverter, an improved finite set model predictive control method is proposed based on the mixed logical dynamical (MLD) model to the new inverter circuit. In a control period, the original 8 voltage vectors are combined with the other one to increase the number of vectors, and the switch states corresponding to the minimum objective function value is selected as the input to reduce the error between the reference voltage and the output voltage. At the same time, by optimizing the objective function and increasing the control period, the influence of long sampling time and calculation time on the switch state selection is overcome. This method reduces the THD of output voltage and has good dynamic and static characteristics, Simulation and experiment verify the effectiveness of the proposed method.
    Application of Kernel NPE for Fault Detection in Chemical Processes
    LI Chun-yang, XIA Li-sha, LI Jun-xiang
    2020, 27(1):  92-97. 
    Asbtract ( )  
    Related Articles | Metrics
    Chemical production process has the characteristics of high dimension and strong nonlinearity. For the deficiency of traditional neighborhood preserving embedding (NPE) algorithm in feature extraction of non-linear data, a Gaussian kernel function is introduced to transform data from non-linear input space to linear feature space. Kernel neighborhood preserving embedding (KNPE) algorithm can extract the non-linear structure of data better on the basis of constructing local spatial feature structure. By a case study on the Tennessee Eastman (TE) simulation process,  and SPE statistics are constructed for fault detection, which proves that KNPE method can detect the occurrence of non-linear faults faster and more accurately than NPE and KPCA methods.

    Harmonic Frequency Spectra Spread of PMSM Based on Random Space Vector Pulse Width Modulation

    GAO Ying, WANG Jia-jun, SUN Jia-hao
    2019, 26(2):  264-269. 
    Asbtract ( )  
    Related Articles | Metrics
    In the voltage source inverter fed permanent magnet synchronous motor (PMSM) driving system, there exists a large amount of voltage and current harmonic components concentrating around the switching frequency and its integer multiples for the traditional space vector pulse width modulation (SVPWM). In order to reduce the voltage and current harmonics of the inverter, the random carrier SVPWM is applied to spread the frequency spectra. This method can change the distribution of the harmonic components of the VSI and alleviate the acoustic noise, undesirable vibration and electromagnetic interference, which improves the control performance of the motor. Single random carrier space vector pulse width modulation (SRCSVPWM) and chaotic SVPWM are introduced. Simulation results in Matlab/Simulink show the effectiveness of the control method. In order to further prove the effectiveness of the random SVPWM on the frequency spectra spread, this paper evaluates the method by using the harmonic expansion factor (HSF) and the total harmonic distortion (THD).
    Database Platform Architecture Based on “X86 Distributed Storage”
    LUO Wei, RAO Bing, JIANG Po-huang, QI Ming, YAO Ting-ting, JIANG Ya-tong
    2020, 27(02):  303-308. 
    Asbtract ( )  
    Related Articles | Metrics
    With the increasingly prominent information security issues at home and abroad, the need for localization of information system equipment and the independence of information operation and maintenance is increasingly urgent. At the same time, with the continuous deepening of the application of information systems, a significant increase in the number of users and services has caused a bottleneck in system performance, and performance optimization is urgently needed. There are many successful cases in China that are subject to third-party integration companies, with closed source software and low controllability. Therefore, an optimization scheme of X86-based distributed storage architecture platform is proposed. This solution uses distributed storage, multi-node redundancy in computing nodes, storage nodes, and switches. It also uses a dual-active high-availability database system with primary and standby databases, which increases system reliability, reduces operation and maintenance costs, and achieves information Deep autonomous operation and maintenance of communication. The experiments of the feasibility analysis of the optimization method prove that the optimization scheme of the new platform is always better than the existing related optimization schemes.
    Research on Mobile Power Trading Behavior Based on Group Active Learning Algorithm
    WAND Lei, JIAO Ming-hai, DAI Yong, ZHANG Qian
    2019, 26(3):  484-491. 
    Asbtract ( )  
    Related Articles | Metrics
    Mobile power trading information service promotes the business scale of power generation enterprises, sale companies and purchasing users of electricity, it forms multilateral trade member modes in the power market and also realizes multi-category complementary trading between supply and demand. The transaction behaviors of mobile power market members are analyzed, and the KNN algorithm based on group active learning strategy is presented. It is effective to build the training set by the group active learning strategy. Firstly, the unlabeled samples are randomly selected by group to construct a candidate set. Secondly, the individual deviation values for distance cumulative means are computed in unlabeled grouping samples. And then the candidate samples sets are filtered by satisfying the support degree values and added to the training sample set. Finally, the KNN classification algorithm based on the group active learning strategy is proposed as an implementation step description. The case study of the mobile power trading user behavior data is implemented by the proposed methodology, and the person coefficients are computed by characteristics elements with customer satisfaction, region, time, power market clearing price, to classify the most similar power purchasers. Experimental results show that the time and accuracy of group active learning KNN algorithm meet the expected requirements. The proposed active learning algorithm is more effective, and is applicable to analysis and decision on the mobile power trading market.
    Study on Fault Diagnosis for Nonlinear Circuit Based on Lissajous Figures
    LU Jing, CHEN Xin, LI Zhi-Hua
    2019, 26(4):  694-699. 
    Asbtract ( )  
    Related Articles | Metrics
    A method based on the Lissajous figures is put forward in order to solve the defects of fault diagnosis of nonlinear circuits. A Lissajous figure is composed of excitation signals and measurable node signals in the circuit, which can be analyzed by using the curvature energy and feature points of curvature. Then we can get the useful information of Lisasajous figures which will be used to form the fault feature vector. This method has the advantage of combining the information of excitation signals and measurable nodes, and it doesn’t need to analyze the circuit topology. The simulation experiments show that the diagnosis result of the logarithmic amplifying circuit can reach 90 %, which proves that the method has good effect for nonlinear analog circuit fault diagnosis.
    Trajectory Tracking Control for Robot Manipulator Using Fractional Order-Fuzzy-ADRC
    LIU Hong-yan, ZHOU Yan, MU San-min
    2019, 26(5):  892-897. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to deal with the low precision, big stable state error and slow response dynamic of traditional control method on robotic manipulator control, a novel control method based on fractional order-fuzzy control-adaptive disturbance rejection control (FO-FC-ADRC) is proposed to control the robotic manipulator: the tracking differentiator is used to extract the speed and acceleration of manipulator without sensors; the fractional order PID (FO-PID) is adopted to realize the zero error control of robotic manipulator system, which is essentially a fractional order system; the fuzzy is utilized to optimize the parameters of the FO-PID in real time, which can improve the performance of the proposed control. The proposed FO-FC-ADRC is compared with the conventional PID control by simulation, and the results show that the proposed control for trajectory tracking of robotic manipulator is much better than the conventional PID both in dynamic and static performance index.
    Autonomous Mobile Robot Path Planning Based on Improved Artificial Potential Method
    LUO Qiang, WANG Hai-bao, CUI xiao-jin, HE Jing-chang
    2019, 26(6):  1091-1098. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to overcome the shortcomings of artificial potential field method in path planning of mobile robots, an improved artificial potential field method is proposed. The obstacles that outside the range of robot's movement are removed to reduce the amount of calculation; the distance between the robot and the target is introduced in the repulsion function to solve the problem of unreachable target. The tangent method is used to solve the problem of local minima point formed by the action of a single obstacle, and the search method is used to solve the problem of local minima point formed by the simultaneous action of multiple obstacles. Considering the complexity of path planning, an adaptive step adjustment algorithm is proposed. Finally, a simulation experiment is carried out on the Matlab platform. The experimental results show that the improved artificial potential field method can overcome the target unreachable problem and local minimum problem, and at the same time it has a greater superiority in amount of calculation, path planning steps and path smoothness.
    Robust Fault Detection for Asynchronous Traction Motor of CRH5 Electric Multiple Unit
    Traction motor, unknown input observer, load disturbance, parameter uncertainty, robust fault detection
    2019, 26(7):  1315-1320. 
    Asbtract ( )  
    Related Articles | Metrics
    Reliability requirement of CRH5 electric multiple unit is more and more high with its wide application, and fault detection for induction motor is critical as the motor is important part of traction system. Firstly, taking the operating condition of induction motor into consideration, an unknown input observer design method is proposed, which has good robustness for the load disturbance. Meanwhile, the resistance of rotor is varied because of special environment so the system matrix is uncertain, the designed observer must be sensitive to faults and robust to the load disturbance as well as the uncertainty so that it can decrease the missing false rate and the false alarm rate; Finally, the designed unknown input observer is applied to the actuator fault detection of the traction motor, and the effectiveness of the proposed method is proved.
    Active Disturbance Rejection Sliding Mode Controller Design for UAVs Close Formation
    ZHAO Jing-xiang, TANG Bin
    2019, 26(8):  1572-1577. 
    Asbtract ( )  
    Related Articles | Metrics
    For UAVs close formation system with nonlinear, under-actuated and strong coupling, an improved active disturbance rejection sliding mode control algorithm is proposed. First, extended state observer is designed to estimate the uncertainties such as aerodynamic coupling and compensate them in control law. Then, in order to reduce the difficulties of parameter optimization and controlling for under-actuated system, the ADRC is combined with sliding mode control to design the compound controller. Finally, Lyapunov function is used to prove that the tracking error converges uniformly to zero. Simulation results show that the proposed method not only simplifies the design of the controller, but also has high control precision and stronger robustness. The controller can effectively transform and keep formation configuration, and has a good expandability.
    A MPPT Method of Photovoltaic Array Based on Gradient Descent and Differential Evolution Algorithm
    YE Jin, DONG Mei-chen, HE Hua-guang, HU Liang-qing
    2019, 26(9):  1695-1702. 
    Asbtract ( )  
    Related Articles | Metrics
    Under the partial shading condition, the PV curve of the PV array will show the characteristics of multiple power peak points, while the traditional methods for PV array can only track the single power peak point. As it is fail to use these traditional methods to track the maximum power point in all of the multiple peak points under the partial shading condition, the existing research works are mainly based on particle swarm optimization algorithm and differential evolution algorithm. These algorithms have good global optimization ability, but the convergence stagnation problem easily arises in their local search process, therefore an improved algorithm based on adaptive gradient descent and differential evolution algorithm is proposed, which uses the adaptive gradient descent method to perform local search optimization at the later stage searching of differential evolution algorithm. The simulation results show that the proposed algorithm can find the maximum power point accurately and solve the convergence stagnation problem effectively. Compared with particle swarm optimization algorithm and difference evolution algorithm, the average total optimization time of the proposed algorithm is reduced by 52.67 % and 40.05 % respectively, and the convergence rate is further improved.
    Research on the Method of Multi-AUV Formation Control Based on Self-organized Artificial Potential Filed
    CHEN Yang-yang , ZHU Da-qi , LI Xin
    2019, 26(10):  1875-1881. 
    Asbtract ( )  
    Related Articles | Metrics
    In this paper, self -organizing map (SOM) and artificial potential field methods are combined to solve the multi-AUV (autonomous underwater vehicle) formation and obstacle avoidance problem. An self-organized artificial potential filed formation control method is then proposed. First of all, according to the location of the leader AUV, virtual AUVs’ positions are generated. Virtual AUV positions are used as the input vectors of the SOM network for calculation. The output are the positions of the follower AUVs which are able to control the follower AUVs to reach the desired target points. Secondly, considering the formation problem of obstacle avoidance, the artificial potential field method is used to avoid obstacle and re-plan paths for formation. Finally, the effectiveness of the proposed algorithm is verified by simulations.

    Fractional Sliding Mode Control of Mine Motor Based on Load Observation

    HAN Tian-liang, MIU Zhong-cui, YU Xian-fei, ZHANG Wen-bin
    2019, 26(11):  2052-2060. 
    Asbtract ( )  
    Related Articles | Metrics
    Mine electric locomotive is an important transport machine of the mine ground and underground tunnel, its working conditions are complex and has a poor operating environment. In order to improve the traction motor speed control performance and improve the system anti-disturbance and the robustness to the parameter variation, the speed controller of the control system is proposed, which uses fractional sliding mode to replace the traditional PI control. Aiming at load changes in the running process of the electric locomotive, the load torque observer is designed to observe the load torque in real-time, the observed value is integrated into the control strategy, which can improve the speed of the load mutation control. Simulation results show that the load observer can observe the load torque quickly and accurately. The sliding mode speed control with load observer has a strong anti-jamming effect on the load disturbance and effectively restrains the inherent chattering of the sliding mode control.

    Research on Data Driven Modeling of Superheater Temperature Deviation based on Partial Mutual Information

    2019, 26(12):  2205-2210. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to reduce the temperature deviation between different superheater areas in large coal-fired boiler, and to improve the operating safety and stability, a data-driven modeling method PMI-SVR is proposed to describe the superheater temperature deviation. The main factors that affect the superheater temperature deviation are chosen from many on field operation data based on the partial mutual information (PMI) criteria. Then the data driven temperature deviation is modeled using support vector regression (SVR) algorithm. The influences of the algorithm parameters of PMI-SVR are discussed in detail to obtain the optimal model. Simulation results on a 350 MW unit show that the feature selection method based on PMI can effectively obtain the main factors that affect the temperature deviation of the superheater. Based on these variables, the data driven model drawn from the data has high accuracy, and it will be useful for further temperature deviation control.
    Defect Classification of Glass Fiber Fabric Based on Multi-feature Fusion
    ZHENG Min, JING Jun-feng, ZHANG Huan-huan, SU Ze-bin
    2020, 27(1):  98-103. 
    Asbtract ( )  
    Related Articles | Metrics
     Focusing on the problems of low efficiency and poor stability of the traditional glass fiber fabric defect classification method, a glass fiber fabric defect classification algorithm based on multi-feature fusion is proposed. Firstly, the median filter is used to preprocess the glass fiber fabric image to remove the detail noise and reduce the influence of background texture. Secondly, Canny edge detection is performed on the pre-processed image, and Hu invariant moment is used to extract the geometric features of defects. Then, the texture features of the image are extracted by scale invariant feature transform (SIFT). After K-means clustering, the bag of words model (BoW) of the glass fiber fabric image is constructed. Finally, the geometric features and texture features are merged and passed into the SVM for training, and the corresponding glass fiber fabric defect classification model is obtained. The experimental results show that the average classification accuracy can reach 97.22 %, which can meet the actual needs of enterprises.
    Design of Tension Control System for Filament Winding
    2019, 26(2):  270-275. 
    Asbtract ( )  
    Related Articles | Metrics

    Aiming at the requirement of maintaining constant tension in filament winding and the great tension fluctuation in the traditional tension control, the mathematic model is established on the basis of analyzing the tension controller of the pendulum pole. The fuzzy control combined with variable integral PID is taken as the control mode and its feasibility is analyzed. The experiment results show that the control method combining fuzzy control and variable integral PID is applied to the tension control system, the performance is better than the traditional PID control, and the change of the parameter has higher adaptability. It can solve the problems such as large fluctuation of tension in filament winding, low speed of yarn breaking and yarn return.

    Attitude Control of Flapping-wing Aircraft Based on Adaptive Terminal Sliding Mode
    WANG Bing-yuan, ZHANG Shuai-hua, ZHENG Fang, LI Xia
    2020, 27(02):  309-315. 
    Asbtract ( )  
    Related Articles | Metrics
    According to the principle of time scale separation, a terminal sliding mode control method is proposed based on adaptive weighted reaching law to solve the attitude control problem of flapping-wing aircraft with high nonlinearity, internal model parameter disturbance and external disturbance. The inner and outer loop sliding mode controllers are designed by the length of adjustment time. An adaptive weighted reaching law is designed, which combines the advantages of power and exponential reaching law to eliminate chattering and improve the tracking speed of the system. The adaptive control method is used to estimate the model parameter disturbance on-line, which compensates the output of the sliding mode controller and reduces the steady-state error of the system. The simulation results show that the adaptive terminal sliding mode control not only eliminates the sliding mode chattering problem, but also effectively overcomes the impact of external and internal disturbances.
    Short-term Wind Power Forecasting Based on KELM-AdaBoost method
    LI Jun, YAN Jia-jia
    2019, 26(3):  492-501. 
    Asbtract ( )  
    Related Articles | Metrics
    For short-term wind power forecasting, a KELM-AdaBoost method with weight update mechanism for a data set instance is proposed based on ensemble learning theory. The AdaBoost method can automatically learn multiple weak regressors and boost them into an arbitrarily accurate strong regressor, meanwhile, using kernel extreme learning machine (KELM) as the base learner of the AdaBoost method, which only adjusts the output weights of networks by using the regularization least square algorithm to achieve the minimum training error and the unknown nonlinear feature mapping of the hidden layer is represented with a kernel function, and the KELM method not only uses the RBF kernel function, but also uses the permissible multi-dimension tensor product wavelet kernel function. The proposed KELM-AdaBoost method is applied to the single-step direct forecasting of short-term wind power and the multi-step indirect forecasting in different regions respectively, and the validity of the KELM-AdaBoost method is verified by comparing its accuracy with RBF, SVM, ELM, KELM, RBF-AdaBoost, SVM-AdaBoost, ELM-AdaBoost methods under the same condition, the experiment results show that the proposed KELM-AdaBoost method is superior to the existing forecasting methods on the forecasting accuracy, therefore, it contains a huge potential and good application prospect.
    The SOH Estimation Of Lithium Battery Based on Feature Vectors Selected By Mutual Information
    SUN Hao-hao, PAN Ting-long, WU Ding-hui
    2019, 26(4):  700-707. 
    Asbtract ( )  
    Related Articles | Metrics
     Aiming at the small amount of data and nonlinear characteristics of the samples of lithium battery, a method based on mutual information (MI) that chooses SVR model’s input feature vectors is proposed. The error of SVR model’s output is influenced by two factors, including the presentation of input samples and the model’s parameters. Taking into account these two factors, MI method is determined to be used at input samples’ choice. Finally, the mean voltage and maximum and minimum temperature differences in the process of constant current and constant voltage charging are selected as the input feature vector of the model. In addition, the grid search algorithm is selected to optimize the model parameters. Experimental results show that the estimation accuracy and generalization ability of SOH estimation of lithium battery based on SVR of input feature vectors selected by mutual information is better than the BP neural network model.
    Linear Feedback Synchronization Control Method for Fractional Order Chaotic Systems
    WU Chun-mei
    2019, 26(5):  898-902. 
    Asbtract ( )  
    Related Articles | Metrics
    A novel control method for synchronization problem between two fractional order chaotic systems is proposed based on linear matrix inequality (LMI): the basic principles of fractional order math and LMI is presented; the synchronization controller based on error state function and linear feedback is designed, and the stability of the proposed controller is proved based on LMI. The proposed method retains the nonlinear dynamics of the synchronization error system, and accomplishes stable synchronization between master system and slave system via simple linear feedback control. And the parameters of this two systems are not required. Numerical simulations are performed to demonstrate the effectiveness of the proposed method.

    Positive Gait Recognition Method Based on Kinect Depth Data in Occlusion Scene

    2019, 26(6):  1099-1104. 
    Asbtract ( )  
    Related Articles | Metrics

    Aiming at the difficulty of recognizing the obstruction of the human body in public, a method of using Kinect depth data to solve the positive gait recognition in the occluded scene is proposed. First, the image is captured by installing a depth camera at the top of the entrance and exit of the surveillance area, and the image is segmented by the background subtraction method, the RGB color space is normalized to detect and remove shadows to complete the image preprocessing. Then, the periodic changes of the skeleton structure of the lower body area evaluated by the Kinect are extracted from the front view, and the feature sets corresponding to the rear view are extracted from the depth information of the shadow outline. These feature sets retain high-resolution gait action information. Finally, the unidentified frame of a cluttered test sequence is compared with the matched frame of the training sequence to complete the final recognition. Experiments show that this method is computationally efficient and achieves satisfactory results at different levels of occlusion.

    Optimization of Evacuation Routes Under Unexpected Events Based on Petri Net
    MU Hai-bo, SONG Yu-bo
    2019, 26(7):  1321-1327. 
    Asbtract ( )  
    Related Articles | Metrics
    When emergency vehicles are used for evacuation and rescue under unexpected events, the superior evacuation routes should be determined according to the time delay. The travel time of an emergency vehicle on a road section is depended on the traffic flow on this road, and emergency vehicle starting at different time will face different phases when arriving at an intersection, which in turn results in different intersection delays. A generalized timed Petri net model of urban traffic network is established. Considering the uncertainty of signal at intersections and the time dependence of road travel time, a labeling algorithm based on the parameters of Petri net is designed to find the optimal evacuation route for emergency vehicles. Finally, the effectiveness of the method is indicated by a numerical example. For the purpose of comparison, evacuation routes corresponding to different starting time- same marking and same starting time- different marking are listed, which indicates that this method can better reflect the influence of evacuation starting time and traffic flow on evacuation routes.

    Planning of Electric Vehicle Charging Station Based on Culture Algorithm

    WANG Yv-hong, WANG Zhi-guo, QIU Wei
    2019, 26(8):  1585-1591. 
    Asbtract ( )  
    Related Articles | Metrics
    Uncertainty information and processing in the location problem of electric vehicle charging station is a difficult point in planning, so we have to pay extra attention to the influence of the geographical information, grid loss, uncertain load and so on. An optimal function has to be established by considering the comprehensive expense of the geographical information, the construction cost and the operation cost. This objective function aims to reflect the essence of the electric vehicle charging station planning problem in terms of the constraints of the service radius and the charging demand. In addition to establishing this function, due to the randomness and fuzziness of the uncertain factors, we have adopted the random fuzzy techniques into our proposed model. At the same time, the introduction of chaotic sequences further optimizes the algorithm. Case analysis shows the feasibility and superiority of our proposed algorithm.

    Moving Object Detection Methods Based on Adaptive ViBe

    GUO Ying-chun, YANG Fei-fei , SHI Shuo
    2019, 26(9):  1703-1711. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to solve the problems of fixed parameter setting and ghost, an adaptive strategy for the ViBe(Visual Background Extractor) motion object detection algorithm is proposed, which includes three improved adaptive methods. First, for the sample selection, it expands the sample neighborhood with the uniform random number, which can avoid to select pixels repeatedly and reduce pixel error classification. Then for fixed match radius and background updator in ViBe, adaptive strategies are used respectively that matching radius are set by the degree of dynamic background and background updator is dynamically regulated by the motion velocity. Finally the optimal threshold of quadratic discriminant obtained by an iterative method is used to filter out the misjudgment area and eliminate the ghost areas. Compared with frame difference method, GMM(Gaussian Mixture Model), CodeBook, LSD(Low-rank and Sparse Decomposition), DECOLOR (Detecting Contiguous Outliers in the Low-rank Representation), and ViBe algorithm on the two public video datasets, Change Detection and LASIESTA, the proposed method has a better performance and it is robust for moving object detection in complex background.
    Research on Management and Decision-making Based on Big Data
    2019, 26(10):  1882-1891. 
    Asbtract ( )  
    Related Articles | Metrics
    This is the age of big data, which brings new opportunities for a lot of industries. The combination of big data technologies and decision-making theories changes the conventional decision modes, thereby providing a new trend for development. This paper mainly researches on management and decision-making based on big data, and the constructions are as follows: Firstly, the development and current trend of the big data management are analysed here with respect to three aspects, namely the parameter, the graduation and the technology. Then, on this basis, the development history of decision-making theories is figured out, and the research status of data-driven decision-making is analysed. In order to develop a unified framework, the current models of management and decision based on big data are summarized, and the related application status with some instances is discussed. In the end, some challenges that the management and decision may face in this era are discussed, and some possible trends are presented.

    3 - DOF Helicopter Control Based on Variable Universe Fuzzy PID

    DAI Bo, ZHOU Ze-yu, CHEN Ya-feng, LI Yan-fei
    2019, 26(11):  2061-2066. 
    Asbtract ( )  
    Related Articles | Metrics
     Fuzzy control is an effective method to solve the stability of 3-degree of freedom helicopter system, but when the fuzzy rules are determined, there is a problem of local optimization only for a certain working area, and the fuzzy controller can't guarantee the high-precision tracking of the system trajectory. The variable domain fuzzy PID controller is designed. By adjusting the domain through the expansion factor, it adjusts the domain on the basis of the initial fuzzy rules, increases the application scope of the rules, obtains higher control accuracy, achieves the self-adaptive effect, and realizes the global optimization of the system. The experiment shows that the variable domain fuzzy control can better suppress the steady-state error, improve the response speed and realize the stable operation of the system.

    Research on Energy Management for Ultracapacitor/Lithium Battery Hybrid Electric Vehicles

    SONG Shao-jian, WEI Ze, Liu Yan-yang, LIN Qing-fang, LIN Xiao-feng
    2019, 26(12):  2270-2275. 
    Asbtract ( )  
    Related Articles | Metrics
    The scheme of ultracapacitor/lithium battery hybrid power supply for pure electric vehicle is an effective method to solve the problem of its dynamic performance and economy, but the energy dispatching strategy of the dual energy electric vehicle is close related to its performances, such as energy efficiency of the entire vehicle and the safety of the battery. Therefore, a hybrid electric vehicle testbed with LiFePO4 battery packs(B) and ultracapacitors(C) was studied in this paper. Firstly, the model of the testbed was developed in ADVISOR. Then, an energy dispatching strategy was proposed based on fuzzy logic, and compared with the strategy based on logic threshold in the discharge current, power of battery, energy recovery and energy consumption etc. The simulation and test results show that the hybrid electric vehicle with fuzzy logic energy dispatching strategies can get better performances in the vehicle’s dynamic performance, economy and battery’s safety so on.

    Design of a Banknote Thickness Sensor Based on Eddy Current Principle

    ZHAO Zuo-xi, LIU Xiong, XIAO Can, PAN Xiang, LAI Qi, KE Xin-rong
    2020, 27(1):  104-108. 
    Asbtract ( )  
    Related Articles | Metrics
    The counting machine mainly relies on magnetic safety line, magnetic ink, optical characteristics to identify counterfeit banknotes. Some counterfeit or old banknotes which stick transparent adhesive tapes with different sizes and positions should also be distinguished, but it’s difficult to identify them through existing technology. A multiple section mechanical thickness sensor is designed to convert the thickness of paper money into mechanical displacement, by using the precise displacement sensor based on the LDC1000 inductive digital converter provided by TI company to realize the positioning detection of the thickness of different parts of banknotes. Firstly, the structure and working principle of the mechanical thickness sensor are described. Then introduces the sensor circuit system that designed with the tool of WEBENCH ® Designer LDC1000 provided by TI company. The preliminary test results show that, the resolution of the sensor is better than 5μm in the range of 1 mm and the detection rate reaches 10kHz. The design meets the requirements of banknote thickness detection.

    Attitude Stabilization Backstepping Sliding Model Control in Non-cooperative Target Capturing Process

    YIN Chun-wu, LIU Su-bing
    2019, 26(2):  276-281. 
    Asbtract ( )  
    Related Articles | Metrics
    A robust attitude controller has been designed for the rigid body spacecraft to satisfy the demand of rapid attitude stability with bound external disturbance and rotational inertia perturbance. The changing characters of the rotational inertia in the process of spacecraft capturing non-cooperative target is analyzed. A state feedback controller is designed for the kinetics equation, to ensure the attitude angle stabilize quickly. Then, a sliding mode controller is designed for the dynamics equation, to offset the strong external torque disturbance and system parameter perturbance. Finally, theoretical analysis certifies that the closed-loop system is global asymptotic stable under the robust controller. Under the strong uncertain simulation environment, in which, each sample point will produce a bounded random perturbance, simulations verify the controller performance of speedability, strong robustness and low energy.
    Bottleneck Analysis and Space-time Optimization of Terminal Security Check Throughput
    HU Yan-min, JING Ru-dong, WANG Fan, GUAN Jing, SONG Qing-gong
    2020, 27(02):  316-322. 
    Asbtract ( )  
    Related Articles | Metrics
    Terminal security throughput has been the focus of attention. In order to optimize airport security procedures, reduce the number of security channels and reduce operating costs, an optimization model based on Petri net and queuing theory is proposed. The homogeneous Markov chain is built by using Petri nets, and the screening process is analyzed. The token, library, change of Petri nets model respectively mapped to passengers and baggage, their state and each step of the security. The weight of limiting factors on security procedures is analyzed and the security check process bottlenecks is found out. So a new model is put forward, and verify its reliability. Based on the reliability of the model, the security check layout is analyzed and its layout is adjusted. The results show that the standard deviation of token number and transition utilization in Petri net decreases, and the waiting time tends to equalization, which improve the efficiency. According to queuing theory, the number of open channels is optimized, and corresponding improvement measures are given.
    Integrated Multi-objective Optimization for Outbound Logistics in Iron and Steel Industry
    LIU Li-ping, LI Kun, TIAN Hui-xin
    2019, 26(3):  502-509. 
    Asbtract ( )  
    Related Articles | Metrics
    To handle the low efficiency and high transportation cost of the outbound logistics in iron and steel enterprises, the consolidation planning and transportation scheduling are integrated for optimization. A multi-objective mixed integer programming model is formulated for this problem. According to the characteristics of the problem, a multi-objective variable neighborhood search algorithm is proposed. The characteristics of consolidation planning and transportation scheduling are taken into account so as to achieve the integration and coordination of the two sub-problems. Computational results based on simulated instances illustrate the efficiency of the proposed algorithm.
    Finite-frequency Model Reduction of Linear Switched Systems Via Balanced Truncation 
    DU Xin, WU Xing-cong, HU Zheng , LIU Yuan
    2019, 26(4):  708-716. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the approximation performance over a pre-specified finite frequency interval for the model order reduction problem of linear continuous-time switched systems, this paper develops a parameterized frequency-dependent balanced truncation method. Firstly, the generalized finite-frequency   performance index is introduced to describe the approximation performance over finite-frequency ranges. Then, the finite-frequency performance for both the continuous-time linear switched system and the corresponding parameterized frequency-dependent mapped discrete-time systems is established. Furthermore, the frequency-dependent balanced truncation algorithm is proposed to generate the desired reduced order model. Finally, a numerical example is given to show the effectiveness of the proposed approach.

    Adaptive Control for Hypersonic Gliding Vehicles with Unknown Parameters

    ZHANG Yuan, DONG Xi-wang, LI Qing-dong, REN Zhang
    2019, 26(5):  903-909. 
    Asbtract ( )  
    Related Articles | Metrics
     HGVs (hypersonic gliding vehicles) have the obvious characteristics like high-dynamic, large flight envelop, complex flight environment and so on, in the reentry stage. These features result in severe parameter uncertainties. In order to improve the attitude control performance in the reentry stage, this paper studies the sources of the uncertainty and the unknown parameters, and investigates the adaptive control method for the unknown parameters of hypersonic flight vehicles. A nominal controller is constructed by using the approach of nonlinear dynamic inversion. A nonlinear extended state observer is introduced to estimate the unknown parameters. A compensation controller is built based on the observer. Then, the nominal controller and compensation controller are used together to guarantee the tracking attitude performance of the HGV. To verify the rationality of this method, a simulation test design is presented in light of the longitudinal attitude movement model of hypersonic flight vehicles. This simulation validates the method and shows its advantage in attitude tracking control.
    Cognitive Method Research with Simulated Feedback Regulation Mechanism  for Chinese Character#br#
    #br#
    LI Wei-tao, SONG Cheng-nan, WANG Guang-xin, WANG Jian-ping, DING Mei-shuang
    2019, 26(6):  1105-1111. 
    Asbtract ( )  
    Related Articles | Metrics
    For the drawbacks of existing open-loop cognitive model and closed-loop feedback cognitive model with determinative cognition approach, an intelligent cognitive model with simulated feedback regulation mechanism and multi-cognition approach fusion is explored in this paper, to simulate human cognitive process of free regulating cognitive approaches in the face of various cognitive demand, with repeating intercomparison and deliberately from global to local cognitive characteristics. Firstly, an intelligent cognitive model with simulated feedback regulation mechanism and multi-cognition approach fusion is proposed, the structure and function of the model are proposed, and the operating mechanism of the model is designed. Secondly, the cognitive demanding of samples is analyzed to achieve the adaptive regulation from global to local of cognitive approaches to guide the establishment of optimized feature space and classified cognitive rules. Thirdly, the similarity index of cognitive result is defined to evaluate the credibility of cognitive outcomes to update the cognitive demanding of samples. Finally, the proposed model is applied to the offline handwritten Chinese character cognition. Based on the simulation experiment on GB 23122 - 80 handwritten Chinese sample library, the average cognitive accuracy of this method is 92.78 %. The experimental results show the superiority of the method.

    Research on Obstacle Avoidance Algorithm for Mobile Robot Based on Hybrid Strategy

    ZHANG Qian-qian, YU Dao-yang, LI Min-qiang
    2019, 26(7):  1328-1334. 
    Asbtract ( )  
    Related Articles | Metrics
    A new hybrid real-time obstacle avoidance strategy based on VFH (Vector Field Histogram) and neural network algorithm is proposed according to traditional obstacle avoidance algorithm. In this strategy the vector field histogram method is used to achieve obstacle avoidance firstly, while obtaining a large number of data sets. And a neural network predictor can be obtained by training the data sets. Thereby by this algorithm it can achieve the effect of simultaneously predicting and controlling the motion vector. In order to verify the effectiveness of the strategy, simulation is carried out for different obstacles, and comparing with the single obstacle avoidance. The simulation experiment verifies the feasibility and superiority of this real-time obstacle avoidance strategy.
    Research on Power Plant Thermal Energy Combined Cycle Control Based on CNN Prediction
    Ren Zhi-ling, Zhao Bo-ya
    2019, 26(8):  1544-1549. 
    Asbtract ( )  
    Related Articles | Metrics
     In order to improve the precision and stability of thermal cycle control in power plant, a new model based on convolution neural network was proposed. Firstly, according to the thermal cycle control problem, design the adaptive thermal cycle learning model using convolutional neural network(CNN), the problem that the identification model can not be adjusted adaptively according to the actual working condition is solved, improve the prediction accuracy of the model; Secondly, the state feedback adaptive controller is designed for the designed control system, and the asymptotic stability of the controller is proved, which provides a theoretical basis for the application; Finally, the simulation test on the boiler and turbine combined cycle control in the power plant shows that the proposed method is superior to the traditional PID control algorithm and the generalized predictive control algorithm. And the convergence rate is relatively faster, with better control performance.

    Regularized Nonnegative Matrix Factorization based on L21 Norm

    LI Cheng, ZHAO Hai-lin
    2019, 26(9):  1712-1716. 
    Asbtract ( )  
    Related Articles | Metrics

    Non-negative matrix factorization (NMF) adds non-negative constraints to matrix decomposition, and its decomposed sub-matrices are easier to interpret. The optimization target of many traditional NMF algorithms is based on L2 norm, and they are not easy to identify the nonlinearly distributed data structures. In order to solve this problem, we propose a regularized non-negative matrix factorization algorithm based on L21 norm. The objective function of the proposed algorithm is written into the form of L21 norm, and we add graph regularization term to the objective function to handle complex nonlinear data sets. Finally, several benchmark data sets are used to test the performance of the proposed algorithm on the clustering task. The experimental results show that the proposed algorithm can extract the key features of the data, obtain the low-dimensional representation of the original data, and produce better clustering results.

    Data-driven Vessel Smart Fault Diagnosis method
    JIA Bao-zhu, JIA Zhi-tao, YU Pei-wen, AN Lian-tong
    2019, 26(10):  1892-1898. 
    Asbtract ( )  
    Related Articles | Metrics
     There are huge of data in the engineroom integrated monitoring and control system, which prognosis the health and fault status of system. Aiming at the redundant condition attributes in raw datum, the equivalence attribute is defined based on rough set, and an effective attribute reduction method is proposed depend on equivalence attribute. The basic probability and evidential decision coefficient are used to measure the contribution of condition attribution to decision attribution. According to this, the minimization attribute decision table is derived after evidential reasoning. The calculating example with sample datum of central cooling water system shows that the proposed method is effective for system hidden fault diagnosis.

    A Method of Batch-to-batch Adaptive Optimization Based on T-PLS

    SHEN Jian , CHU Fei , DAI Wei , JIA Run-da, MA Xiao-pin
    2019, 26(11):  2067-2072. 
    Asbtract ( )  
    Related Articles | Metrics

    In this paper, an adaptive batch optimization method based on T-PLS is proposed to apply to the quality control and optimization of batch process. Due to the complexity of batch process, the model can’t perfectly match with the plant and result to NCO mismatch, in which the optimization result is just suboptimal. The gradient correction method is used to compensate the differences between the model and the plant. At the

    same time, in order to expand the effective range of control variables, T-PLS statistics (,,) are

    introduced as a hard constraint. Finally, the simulation is carried out to verify the effectiveness of the proposed method.

    Study on the Control System of the Automatic Abrasive Blasting Robot for the Large Diameter Bend Pipe

    YUE Long-wang, LIU Bao-guo, CHEN Xing-zhou, WANG Zong-cai
    2019, 26(12):  2276-2281. 
    Asbtract ( )  
    Related Articles | Metrics
    Automatic abrasive blasting system is an important equipment to realize automatic abrasive blasting of steel pipe, and the quality and efficiency are important features of the system. Focused on surface tracking problem of automatic blasting of pipe bends, the control system of the automatic abrasive blasting robot for large diameter bend pipes was studied. According to the 5-DOF abrasive blasting robot of orthogonal coordinates, the control system was designed with PLC as the main controller; the model of the surface tracking was constructed based on the infrared range sensors; based on the least square method, the second order linear fitting method was used to calibrate the infrared range sensors, and the verification experiment was made. This study is of great significance to raise the quality and efficiency of the abrasive blasting, reduce the labor intensity and improve the working environment.
    Iterative Learning Based Control for Wind Tunnel Mach Number
    YI Fan, LI Xin-rui, DU Ning, YU Wen-shan
    2020, 27(1):  109-113. 
    Asbtract ( )  
    Related Articles | Metrics

    Sliding Mode Control for 3D Path-following of Underactuated AUV

    WANG Xiao-wei, YAO Xu-liang, BU Su-wen, WANG Feng
    2019, 26(2):  282-288. 
    Asbtract ( )  
    Related Articles | Metrics
    To deal with the problem of 3D path-following control for underactuated autonomous underwater vehicles (AUV). Virtual guidance law is introduced based on Serret-Frenet frame, the 3D path-following kinematic error model is established on the basis of considering the angles of attack and sideslip. First of all, the kinematics controller is designed according to the theory of Lyapunov by introducing two approaching angles. Then the dynamic controller is developed based on the theory of sliding mode control (SMC), so that the asymptotic stability and robustness of the control system can be guaranteed. In order to reduce chattering, the uncertainty of the model is estimated through the disturbance observer. Simulation results show that the controller has good robustness to the model parameter uncertainty. Accurate tracking of the 3D path can be realized.
    Simulation and Profit Decision on Quality Control Model of Four Levels Closed-loop Supply Chain
    DONG Hai, XU De-min
    2020, 27(02):  323-328. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at the four levels closed-loop supply chain system composed of suppliers, manufacturers, sellers and third-party recycling, the system dynamics method is used to solve the quality control problem of four levels closed-loop supply chain. Firstly, the cause-and-effect loop diagram of four levels closed-loop supply chain quality control is plotted by Vensim simulation software, and the relationship between the influencing factors and the model boundary are found out. Secondly, the equations of each variable are designed, and the system flow diagram and the quality control model of the four levels closed-loop supply chain are further established. Meanwhile, rationality and authenticity of the model are tested. Finally, a numerical example is carried out to verify that the improvement of raw material quality fluctuation level and service quality level can improve the total profit of members at all levels of the four levels closed-loop supply chain, and it also can improve the overall performance of the closed-loop supply chain.
    Cooperative Hunting Strategy for Multi-mobile Robot Systems Based on Dynamic Hunting Points
    LI Rui-zhen, YANG Hui-zhen, XIAO Cong-shan
    2019, 26(3):  510-514. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to surround the moving target by hunting agents beneficially, a multi-agent cooperative hunting strategy based on dynamic hunting points is proposed. Desired hunting points are configured dynamically according to the position of the target and the negotiation mechanism is applied to allocate the desired hunting point for each mobile agent. A cost function is established to integrate the path consumption and the surrounding effectiveness. The desired orientation angle for each agent is obtained by optimizing the cost function. Finally, the online path planning of the robot is realized. Simulation results show the effectiveness of the proposed hunting strategy.
    A Novel Nonsingular Fast Terminal Sliding Mode Control with Adaptive Boundary Layer
    ZHANG Bei-bei, ZHAO Dong-ya, GAO Shou-li, ZHANG Jia-shu
    2019, 26(4):  717-723. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to solve the problem that the conventional nonsingular fast terminal sliding mode (NFTSM) control converges slower than classical terminal sliding mode (TSM) control. A novel NFTSM is proposed for nonlinear uncertain systems and faster convergence rate is achieved especially in the neighbor of equilibrium points in comparison with the classical TSM control. Then, a novel NFTSM control with adaptive boundary layer is proposed so as to make systematic variables converge to a residual set in finite time. Furthermore, the application of adaptive boundary layers achieves higher precision and stronger robustness. The stability of closed loop systems is confirmed by Lyapunov theory. Finally, the simulation results verify that higher control precision and superior systematic robustness can be obtained simultaneously by the proposed approach for nonlinear uncertain systems.
    Improved Application of Complementary Filtering in Three-dimensional Attitude Estimation
    CHEN Wei, ZHAO Ming, CHEN Mei
    2019, 26(5):  910-915. 
    Asbtract ( )  
    Related Articles | Metrics
    In the process of attitude calculation of the four axis aircraft, the attitude angle is solved by fusing the multi sensor data. However, there is a problem that the yaw angle of quad - rotor aircraft will change the pitch angle and roll angle in the application of the complementary filtering algorithm to 3D attitude calculation. Aiming at the problem, The solution process of 3D attitude angle of four axis aircraft is analyzed in detail, the improvement of 3D attitude calculation algorithm is also presented, the error compensation component of the complementary filter is modified, the error compensation of the Y axis and the X axis is removed, and the error compensation of the Z axis magnetometer is added. The experimental platform includes STM32 controller, MPU6050 and AK8975 attitude sensor, which the validity of the improved algorithm is verified on. The experimental results show that the improved attitude algorithm can solve the 3D attitude angle of the four axis vehicle in real time and solve the problem of the mutual interference between the attitude angles.

    A Combined Particle Filter for Multiple Extended Target Tacking

    HAN Yu-lan, HAN Chong-zhao, XUE Li
    2019, 26(6):  1112-1117. 
    Asbtract ( )  
    Related Articles | Metrics
    To track extended targets for the linear Gaussian system, the multiple extended target Rao-Blackwellised particle filter (RBPF), which estimates the data association and multiple target states jointly, is proposed. The proposed filter applies the particle filter to estimate the data association, and employs the extended target filter based on random matrix to estimate kinematic states and shape information of extended targets. First, the framework of the multiple extended target RBPF is proposed. Then, the joint proposal distribution for the association hypothesis is defined. Furthermore, the Bayesian framework of multiple extended target tracking is implemented by the combined filter, which applies the particle filter and the extended target filter based on random matrix. In comparison with the multiple extended target filter based on JPDA algorithm and the multiple extended target filter based on probability hypothesis density, simulation results show that the multiple extended target RBPF achieves the less error of the shape estimates, and enhances the position tracking accuracy in the situation that there are spatially close extended targets.
    Improved Low Frequency Oscillation Analysis Based on Multi-signal Power System
    WANG Yu-hong, DONG Rui
    2019, 26(7):  1335-1340. 
    Asbtract ( )  
    Related Articles | Metrics
    Using EMD method to denoise the low frequency oscillation signal of the power system with low signal-to-noise ratio, there will be a large error, affecting the identification accuracy of low-frequency oscillation signal. In order to solve these problems, an improved EMD denoising method is proposed in this paper. The   IMF modal components are obtained by EMD decomposition of the low frequency oscillation signal of the power system, the normalized autocorrelation functions are obtained and the demarcation point   between noise dominant mode and signal dominant mode is determined. Then, the noise dominant mode is denoised, and the denoised components are reconstructed with the signal dominant mode to obtain the power system low frequency oscillation signal. Finally, multi-signal Prony analysis of reconstructed signals is carried out to extract the characteristics of low-frequency oscillation in power system. The experimental results show that the improved EMD method is more effective for low frequency signal denoising with low signal-to-noise ratio (SNR), the improved EMD method and the multi-signal Prony algorithm are applied to improve the performance of the EMD multi-signal Prony algorithm. The characteristics of low-frequency oscillation signal in power system have the advantages of fast speed, high resolution and good fitting effect.
    Process Monitoring Method Based on Adaptive Threshold PLS and its Application
    LIANG Meng-yuan, ZHOU Ping
    2019, 26(8):  1437-1443. 
    Asbtract ( )  
    Related Articles | Metrics
    Partial least squares (PLS) has been extensively researched and applied in industrial process monitoring. In order to improve the monitoring effect based on PLS process monitoring, aiming at the problem that the traditional PLS method uses a fixed threshold which generates a lot of false alarms and missed detections, an adaptive threshold PLS process monitoring method is proposed. Firstly, the PLS monitoring model is established according to the normal historical data of the process, and the corresponding adaptive threshold is calculated according to the exponentially weighted moving average of the statistics for the process monitoring. Finally, using the Tennessee Eastman (TE) process and large blast furnace iron-making process simulation experiment to test the performance of the method. The experimental results show that the process monitoring based on adaptive threshold PLS can reduce the false alarms rate and improve the process monitoring performance compared with the traditional PLS method.
    Performance Analysis of Regulation Schemes for LLC Resonant DC/DC Converters#br#
    #br#
    DING Ben
    2019, 26(9):  1717-1721. 
    Asbtract ( )  
    Related Articles | Metrics
    LLC resonant converter is widely used with many advantages such as high efficiency, small volume and low loss. Based on the working principle analysis of LLC resonant-based DC/DC converter, the modulation strategy of LLC resonant DC/DC converter is designed. The performance analysis including closed-loop performance, frequency domain performance, and conduction losses for the two regulation schemes (predominantly pulse-width modulation and pulse-position modulation) are carried out with PSIM 6.0 software. In these two modulation control schemes, both the two switches of half-bridge inverters are controlled by square-wave pulses with the dead-time of 250 ns, thus avoiding short-circuit of the two switches. Simulation results indicate that over a wide range of load variation, the predominantly pulse-position modulationscheme has better performance of frequency selection at high input voltage, which makes it more suitable for the design of DC/DC converter and the improvement of performance of power conversion system.
    Performance Assessment of Parallel Cascade Control System Based On Minimum Entropy
    LIU Yang , WANG Ya-gang
    2019, 26(10):  1899-1904. 
    Asbtract ( )  
    Related Articles | Metrics
    Cascade control is a frequently used control strategy in industrial processes. It can reduce the maximum deviation and the integral error compared with the single loop. Currently, the minimum variance method of parallel cascade control system are developed based on the assumption that all the disturbance are subject to Gaussian distribution. However, in the practical condition, some disturbances do not obey the Gaussian distribution. The minimum entropy index of performance assessment of the parallel cascade control system subjected to non-Gaussian disturbances is proposed. In the stochastic process, the information entropy has more general significance than mean or variance for any random variable. The estimated ARMA model for the parallel cascade control loop based on the minimum entropy instead of the minimum mean squares error has better performance for non-Gaussian disturbances. The result of proposed methods are demonstrated through a simulation example. 

    Route Planning Based on Programmed Cell Death Evolutionary Algorithm

    ZHANG Xiao, LIU Zuo-jun, CHEN Ling-ling, YANG Peng
    2019, 26(11):  2073-2077. 
    Asbtract ( )  
    Related Articles | Metrics

    The mechanism of programmed cell death is simulated in evolutionary algorithm. Three artificial control genes are introduced for the optimization of the traditional genetic algorithm. The advanced achievement of biology is absorbed in this new evolutionary algorithm. It can effectively overcome the premature problem of genetic algorithm. Besides, it can also obtain both the optimal solution and several sub optimal solutions. The the feasibility and effect of the algorithm is tested in the vehicle route planning.

    Guaranteed Cost Preview and Repetitive Control for Uncertain Linear Discrete Systems

    LAN Yong-hong, LIU Li, XIA Jun-jun
    2019, 26(12):  2282-2288. 
    Asbtract ( )  
    Related Articles | Metrics
    For a class of uncertain linear discrete systems with external disturbances, a design method of guaranteed cost repetitive controller with preview compensation is proposed. In order to improve the tracking precision, the repetitive controller is introduced in the forward channel, and the augmented error system that includes the preview information of the target signal and the disturbance signal is obtained by using the difference operator. On the basis of this, the guaranteed cost preview repetitive control problem is transformed into a guaranteed cost control problem for a class of linear discrete systems. Furthermore, the design method of the guaranteed cost controller is obtained by using the Lyapunov method and the linear matrix inequality techniques. Finally, the effectiveness of the proposed method is verified by a numerical example.
    Robust Disturbance Rejection Control of SCR Denitration System
    MA Zeng-hui, XU Hui-yi, ZHU Run-chao
    2020, 27(1):  114-120. 
    Asbtract ( )  
    Related Articles | Metrics
    Selective catalytic reduction (SCR) technology is widely used for flue gas denitration of thermal power plants. The SCR denitration system is very complex and SCR system has the characteristics of large inertia, dead-time, strong disturbance and uncertainty. So, it is almost impossible to achieve precise control of the amount of ammonia injection by the traditional PID control scheme. In this paper, a robust disturbance rejection control method for SCR denitration system is presented. Based on the design of robust PID controller, robust time-delay filter is used to suppress the strong disturbance of the system. The simulation results show that the addition of robust time-delay filter improves the dynamic performance of the system and makes the system has outstanding disturbance rejection performance. The scheme proposed in this paper has simple structure, easy parameter tuning and good robustness. It is worth popularizing in engineering.

    Nonlinear Proportional Back-stepping Control for a Class of Pure Feedback Systems

    Chen Long-sheng
    2019, 26(2):  288-294. 
    Asbtract ( )  
    Related Articles | Metrics
    A novel control approach based on the combination of back-stepping design and nonlinear proportional control is presented for a class of uncertain pure feedback systems. Based on the double performance functions, the nonlinear proportional controller is developed. Meanwhile, during every step of back-stepping, a Nussbaum function and a nonlinear proportional controller are adopted to construct the nonlinear proportional back-stepping controller to satisfy the requirements of unknown parameters, unknown structure, unknown control direction, unknown initial states and prescribed performance. The design procedure and structure of the proposed scheme are very simple with least adjustable parameters. Finally, the stability of the close-loop system is proved based on Lyapunov stability theorem. The simulation results demonstrate the feasibility and validity of the proposed control schemes.
    Optimization of Warehouse Layout Based on Improved Clonal Selection Algorithm
    CAO Xia, CAO Min
    2020, 27(02):  329-334. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to overcome the defects existing in the optimization strategy of warehouse layout problem, this paper proposes an improved clonal selection algorithm based on the introduction of vaccine strategy. This algorithm adopts roulette algorithm in the process of vaccine selection and vaccination. Cloning scale, combining antibody affinity and antibody concentration, is calculated in the process of cloning and proliferation. The algorithm also retains excellent antibodies during cloning inhibition and introduces random antibodies. These optimization strategies which improve the convergence speed and optimization efficiency of the algorithm and increase the population diversity are used to realize the storage layout which satisfies the demand of the access job and the given condition constraint. Simulation analyses and comparisons show that this algorithm has the characteristics of faster convergence speed and shorter access path, thus greatly improving storage efficiency.
    Signed Directed Graph and Qualitative Trend Based Model Semiquantitative Validation
    GAO Dong, XU Xin
    2019, 26(3):  515-520. 
    Asbtract ( )  
    Related Articles | Metrics
    For the traditional model validation methods, the completeness is weak and it depends on human experience. The signed directed graph (SDG) and qualitative trend based model semiquantitative validation is proposed. First, the SDG model is built and qualitative trends are added to the model. Then complete testing cases are produced by positive inference. The semiquantitative validation is carried out by comparing the testing cases with outputs of the simulation model in different scales. Finally, the effectiveness is proved by carrying out validation for a reactor model.
    Twelve-section Direct Thrust Force Control for Permanent Magnet Linear Synchronous Motor
    ZHANG Hong-wei, WANG Xin-huan, CHEN Kai-bin
    2019, 26(4):  729-734. 
    Asbtract ( )  
    Related Articles | Metrics
    To deal with the defect of thrust ripples of the traditional six section direct thrust control (DTC) for permanent magnet linear synchronous motor (PMLSM), a novel DTC strategy of PMLSM combined 12 stator flux linkage sectors and 13 voltage space vectors is proposed. A novel voltage selection table is designed. The way of three and two devices conducting interactively is applied to realize 13 voltage space vectors. The method is simulated through Matlab/Simulink. The results of simulation verify the better performance of the twelve-section control method, which can reduce the thrust and flux linkage ripple.
    2-DOF Joint Robot Trajectory Control System Based on Port-Controlled Hamiltonian and PD Algorithm Coordinate Control
    CHI Jie-ru, YU Hai-sheng, YANG Jie, NIU Huan, ZHANG Qi-gao
    2019, 26(5):  916-921. 
    Asbtract ( )  
    Related Articles | Metrics
    A hybrid coordinated control method based on Port-controlled Hamilton (PCH) and PD algorithm is designed to solve the problem that a single control method cannot effectively realize the trajectory tracking control of a 2-DOF joint robot. The Port-controlled Hamilton (PCH) control is used to ensure the stability of the system, and the traditional PD control is used to improve the response speed of the system. The exponential function is used as the coordination function to realize the coordinated control strategy of the 2-DOF joint robot, so as to adapt to the error interference of the 2-DOF joint robot. The control system not only achieves fast tracking control, but also makes the output signal of the robot in a higher error precision range. The simulation results show that, even if there are errors in the mechanical system modeling of the robot, the proposed coordinated control method can make the system not only have good dynamic and steady-state performance, but also eliminate errors quickly.
    Observer Based Control for Nonlinear Single Joint Manipulator System
    DONG Xue-lian, LIAO Jia-min, ZENG Meng-lan, ZHAO Xiong, XIANG Kui-wei, FEI Ling, ZHENG Liang
    2019, 26(6):  1118-1125. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at a class of nonlinear dynamic single joint manipulator system, which subject to disturbance, uncertainty and fault, an observer based sliding mode control (OBSMC) strategy, is proposed. First, the state of the system and disturbance are observed by a composite estimator, and the fault is reconstructed by introducing a sliding mode surface. Second, in accordance with the estimation information, the OBSMC scheme is designed. The sliding surface is constructed with good reaching ability, and the stability of the system is guaranteed simultaneously. In addition, the   performance is introduced to ensure the robustness of the system. Finally, the proposed method is applied to a class of flexible single joint manipulator system. The simulation results show that the observer has a high accuracy of the disturbance and fault signal, and the controller can guarantee the stability of the system, which illustrate the effectiveness of the proposed method.
    Data Access Point Planning of Power Distribution Communication Network with LTE-PON Hybrid Deployment
    CHANG Hai-jiao, LI Xin, XING Ning-zhe, LI Cai-yun
    2019, 26(7):  1341-1347. 
    Asbtract ( )  
    Related Articles | Metrics
    For purpose of promoting the coverage rate of Access Point (AP) in power distribution communication network, an AP planning model and the corresponding solving algorithm in the network composed of PON and wireless LTE private network are proposed. Firstly, the reliability of APs are analyzed according to their importance so that the covering mode can be determined. Secondly, considering the constraints of reliability and budget deployment cost, an AP planning problem model in PON-LTE mixed network is established with the aim of maximizing AP coverage rate. Then, the solution based on a hybrid of multiple intelligent optimization algorithms is proposed for this NP-hard problem. Finally, the proposed method is simulated to show the numerical network performance and the planning effect. The simulation results show that the proposed method owns better performance on coverage rate of AP in the LTE-PON mixed network than the strategies of separately deploying LTE or PON network.

    Research on Anomaly Detection Algorithm Based on Regular Change Background

    YIN Rui, YANG Jian-hua, LU Wei
    2019, 26(8):  1533-1538. 
    Asbtract ( )  
    Related Articles | Metrics
    The mining safety problem of coal bed methane is becoming more and more widely concerned. In order to solve the problem of video monitoring anomaly detection in the coal bed gas mining field, which contains the reciprocating motion of the pump, a new anomaly detection algorithm based on the regular variation background is proposed. In this method, the segmentation algorithm based on the three-frame-difference method is used to divide the image into the static background and the dynamic background of the reciprocating movement of the pump. At the same time, in order to set up the background model, the Surendra algorithm based on the three frame difference is used to extract the static background area information. Then different abnormal detection algorithms are used in different background areas, which can be better to eliminate the normal pump reciprocating movement interference of anomaly detection in the scene. In the static background, the three frame difference method and the background subtraction algorithm are used to divide the foreground. For the dynamic background, the three frame differential method is used to divide the foreground. Experiments show that this algorithm can accurately detect the foreground in coal-bed methane scenes, and meet the requirement of real-time video monitoring.

    Hybrid Supply System Energy Management Strategy of Hybrid Electric Vehicle Based on Adaptive Filter

    YAN Xiao-ming, WANG Da-zhi, LIANG Yu, LI Yun-lu
    2019, 26(9):  1722-1727. 
    Asbtract ( )  
    Related Articles | Metrics

    In order to improve the energy efficiency of the power supply system of hybrid electric vehicle (HEV), an energy management strategy based on adaptive filter is proposed. Firstly, the hybrid power supply system and the bi-directional DC/DC converter of HEV are modeled. Secondly, the adaptive law based on power-split is selected and the novel hybrid power adaptive energy management strategy is designed. Finally, the effectiveness of the proposed method is verified by the simulation experiment under different working conditions. The experimental results show that, the proposed method can transmit power of hybrid power system of HEV effectively to achieve high energy utilization.

    Internal Model Control of Voltage-sourced PWM Rectifier Based on Inverted Decoupling
    LI Xiang-yu, ZHAO Zhi-cheng, WANG Wen-yu
    2019, 26(10):  1905-1910. 
    Asbtract ( )  
    Related Articles | Metrics
    For three-phase voltage-sourced PWM rectifier, a novel double closed loop control method is proposed in this paper, which is based on the mathematical model in synchronous rotating coordinate system. Considering the coupling characteristics, the inner-current loop adopted reverted decoupling internal model control (IMC) method and designed IMC-PI controller for the decoupled generalized controlled object, which could realize the complete decoupling of the nominal systems. On this basis, the IMC-PID controller was designed based on the simplified model of voltage loop. The simulation results show that the proposed method can ensure the complete decoupling of the system, reduce the controller′s tuning parameters, and provide better dynamic performance and robustness.

    Control Strategy of Torque Distribution for Optimizing the Comprehensive Performance of Distributed Drive Electric Vehicle

    HUANG Kai-qi, LUO Liang-quan , CHENG Jian, LIU Xi-Ping
    2019, 26(11):  2078-2087. 
    Asbtract ( )  
    Related Articles | Metrics
    For tackling the problem of the reduction in longitudinal driving torque and the undesired yaw moment when the distributed drive electric vehicle enters the working mode of acceleration slip regulation as well as the motor failure, a torque distribution strategy to reduce the tire utilization rate and improve the longitudinal drive performance is proposed in this paper. The objective function that includes the properties of tire utilization and longitudinal drive is established based on the generalized yaw moment decision, and it is solved by the global sequential quadratic programming (SQP) under the constraints of driving anti-skid, motor failure, maximum driving torque and pavement attachment. A joint control model of distributed drive electric vehicle is established by Carsim and Simulink. The simulation results show that the strategy can improve wheel attachment margin and the vehicle dynamic performance under the premise of ensuring the stability of the vehicle.

    Faults Diagnosis of Three-level Inverter Based on EMD-DTRVM

    TAO Hong-feng, ZHOU Chao-chao, Yang Hui-zhong
    2019, 26(12):  2289-2296. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at the problem of open-circuit fault arising in diode-clamped three-level inverter, a fault diagnosis strategy, based on the empirical mode decomposition and the decision tree relevance vector machine (EMD-DTRVM), is proposed in this paper. First, the operation conditions of main circuit in inverter are analyzed to classify faults, and the inverter bridge voltages are selected as the measured signals. Then, the fault features are extracted in the form of energy and energy entropy by the empirical mode decomposition. Moreover, particle swarm clustering algorithm is used to build the decision tree structure. By training the RVM classified models, the fault diagnosis of power component in three-level inverter is finally accomplished. Compared with traditional approaches, the proposed EMD-DTRVM strategy not only achieves shorter diagnosis time and higher accuracy, but also works simple and efficient with less parameters.
    Research of Electronic Cam Function Block Algorithm Based on PLCopen
    CHEN Mei, WANG Shu-run
    2020, 27(1):  121-126. 
    Asbtract ( )  
    Related Articles | Metrics
     The core of CNC machine tools and industrial robots is motion control system, in order to improve the performance of motion control system, based on the MC motion control specification defined by PLCopen, combined with SoftPLC and motion control program, design and implement the periodic and non-periodic position coordination of electronic cam, and spline interpolation algorithm is used to fit aperiodic curves in non-periodic electronic cam. First, C# is adopted as the programming language to design the framework of function block. Then, C/C++ is adopted as the programming language to carry out motion planning for master axis and combine the discrete points into a curve in the non-periodic condition, the whole control procedure is running in the ProConOS eClR kernel. Finally, the function block is called in the upper platform Multiprog to ensure master axis and slave axis to move cooperatively. The experimental results show that, this kind of cam function block can work not only in periodic condition according to scheduled trajectory but also in non-periodic condition according to key point position, its velocity will not change suddenly, and it has wider application scope.
    Explicit Model Predictive Control of Quad-Rotor Aircraft
    YANG Fan, DIAN Song-yi, WANG Lun
    2019, 26(2):  295-301. 
    Asbtract ( )  
    Related Articles | Metrics
    A binary search algorithm combining the truncated binary tree algorithm and distance search algorithm is proposed to deal with the complex problem of explicit model predictive control (EMPC) in the online search phase. On the basis of the fast binary tree algorithm, the pretreatment time is further reduced by the truncation condition, and then the partition search is performed on the leaf nodes by using the distance search algorithm. Finally, the method is applied to the online phase of the explicit model predictive control of the quad-rotor aircraft. The feasibility of the method is verified by the numerical simulation and the hardware-in-the-loop experiments.
    Research on Optimization of Virtual Machine Deployment Based on Multi Population Genetic Algorithm
    DONG Hao, LI Ye
    2020, 27(02):  335-341. 
    Asbtract ( )  
    Related Articles | Metrics
    In the cloud environment, the virtual machine deployment directly affects the overall performance of the data center. The concept of virtual machines affinity is proposed according to the relationship attributes among virtual machines. And a deployment strategy based on multi population genetic algorithm combined with the penalty function method is applied considering the load balancing of the physical machines and the affinity of the virtual machines. In order to avoid the local optimum, Gauss learning is carried out on the optimal individuals. Simulation results show that the deployment strategy with high load balancing and good affinity could be achieved through the multi population genetic algorithm, which has strong robustness, fast convergence speed and can solve the virtual machine deployment problem effectively in the cloud environment.
    SVPWM Optimization Control of Three-level Inverters
    2019, 26(3):  521-524. 
    Asbtract ( )  
    Related Articles | Metrics
    As to the issue of complex computation for three-lever inverter SVPWM algorithms in Cartesian coordinate system, a SVPWM optimization algorithm in 60 º coordinate system is proposed. This SVPWM algorithm discriminates the regional distribution of hexagonal sectors by the sign of reference vector coordinate, and mappings the reference vector from other sectors to sector I in 60 ºcoordinate system. It discriminates the regional distribution of vector in sector I, and gets the dwell time of base vectors by using algebraic operation. Thus it normalizes the region judgment and dwell time calculation in sector I. The algorithm can effectively reduce the calculation of SVPWM algorithm, and improve the inverter efficiency. The results show that the output of current and voltage in the coordinate system has the same performance as the ideal curve, and the neutral voltage is balanced, and the switching frequency and switching loss are reduced.
    Novel Flux Sliding⁃mode Observer for Direct Torque Controlled Induction Motor Driving Systems#br#
    #br#
    YU Jian-guo, XIAO Hai-feng, XU Yu-hao
    2019, 26(4):  735-739. 
    Asbtract ( )  
    Related Articles | Metrics
    The flux estimation of the induction machine determines the performance of the drive system. The parameters of induction motors are prone to easy impaction with the aid of the conventional flux estimation. A new stator flux estimation is presented, which realizes accurately in the stationary frame of axes by the sliding-mode function. At the same time, the observer of the model contains a rotor-speed-independent term behavior, and estimates the rotor flux and the exact speed of the rotor indirectly. Theoretical analysis and MATALIB simulation results confirm the robustness, accuracy, quick response of the drive.
    Intelligent Penetration for UAV Based on Improved Artificial Fish Swarm Algorithm (AFSA)#br#
    #br#
    ZHANG Guo-feng, ZHOU Kai
    2019, 26(5):  922-926. 
    Asbtract ( )  
    Related Articles | Metrics
    With the risk probability graph used to describe the air defense threat environment faced by UAV penetration, the UAV penetration problem is modeled as the optimal guidance instruction design problem, which minimizes the loss risk of UAV, and the control parameters of mission urgency and damage risk are designed. In order to solve the control model quickly, the fish swarm algorithm is further improved, so that the algorithm has adaptive step-size adjustment mechanism, and overcomes the shortcomings of the convergence speed. The results of simulation and comparative analysis show that the proposed method can make the UAV achieve penetration at a lower cost based on the urgency of mission and the importance of damage risk.
    Design of Intelligent Evacuation Indication System Based on Ant Colony Algorithm
    DONG Hai-yan, DU Xiao-dong, DU Yi-zhi, WENG Zhi-yuan
    2019, 26(6):  1126-1132. 
    Asbtract ( )  
    Related Articles | Metrics
    An intelligent evacuation indication system of the buildings is proposed to find the optimal escape route via the ant colony algorithm. In addition, the proposed system can obtain the accurate information of the fire spot in time by interacting with the fire alarm. Therefore, the overall system is a complete dynamic escape system. The master controller of the proposed system, which is emergency lighting controller designed based on ant colony algorithm, manages the slave emergency power supply and allocates the electric devices and various lamps so as to guarantee the safety and unobstruction of the optimal escape route. The design of all links of the system including the hardware circuit and software flow is presented, and test analysis and experimental results are also given in this paper. The system has a simple and friendly human-computer interaction graphical interface. The concept of the “close evacuation” is changed to the “safe evacuation”, and the integration of measurement, control and management is further realized.

    Application of RBF-ARX Model in the Ship Course-keeping System

    LUO Zhu
    2019, 26(7):  1348-1352. 
    Asbtract ( )  
    Related Articles | Metrics

    Based on the nonlinear characteristic of the ship, it is difficult to obtain accurate physical parameters of the ship physical model. Therefore, the statistical modeling method and RBF-ARX model is used to model the ship course-keeping control process. In this paper, the RBF-ARX model, the ARX model and the long-term predictive output of the physical model are compared, and the effectiveness and superiority of the RBF-ARX model in the ship course-keeping control system modeling are verified.

    Analysis of Track Irregularity Based on the Improved Hilbert-Huang Transform
    ZHAO Ling, HUANG Da-rong, WANG Hong-gang
    2019, 26(8):  1539-1543. 
    Asbtract ( )  
    Related Articles | Metrics
    Dynamics data of the train contains a wealth of information on track irregularities, wheel-rail relationships and so on. Aiming at the high noise component and nonlinear characteristics of the data, an improved Hilbert-Huang analysis method for extracting the transient characteristics of non-stationary signals is proposed. The method draws on the idea of fast band-pass filtering, and obtains the intrinsic mode function through the adaptive band-pass filtering algorithm. It can detect the time frequency, amplitude and other information of transient components in the signal while reducing noise. By using the improved method to process the signal, modal aliasing can be avoided. The research result of the dynamic data of the sample section of the railway has different degrees of short-wave and medium-long-wave irregularities. It shows that the improved Hilbert-Huang transform method can provide a new way to ensure the safe operation of railways.
    Prediction of Sewage Environment Based on GM-RBF
    YANG Zhuang, WU Li, QIAO Jun-fei
    2019, 26(9):  1728-1732. 
    Asbtract ( )  
    Related Articles | Metrics
    Due to the fact that it is difficult to measure the chemical oxygen demand (COD) of sewage water environment parameters, a kind of gray level theoretical prediction model based on radial basis function neural network (GM-RBF) is proposed. The proposed GM-RBF can predict the chemical oxygen demand. The gray theory is used to predict the development and change of the system behavior, and the precision of the prediction model can be improved by combining the high precision approximation ability of the radial basis function neural network. The modeling and prediction of the key water quality parameters in the process of wastewater treatment is studied. The results show that the model can predict the COD with high accuracy, and the prediction is close to the actual value.
    Iterative Learning Control of Multi Inputs and Multi Outputs Gas Tungsten Arc Welding process 
    LIU Jian, BU Xu-hui, LIANG Jia-qi
    2019, 26(10):  1911-1916. 
    Asbtract ( )  
    Related Articles | Metrics
    The welding of same parts have the same welding trajectory, so the welding process has strong repeatability. Aiming at the repeatability of welding process, the tracking control problem of gas tungsten arc welding process with double input and output is studied based on iterative learning control. According to the dynamic model of gas tungsten arc welding, the iterative learning control algorithm of welding process control is designed, and the convergence of the algorithm is analyzed. It turns out that the repeated information of welding can be used effectively by the iterative learning control in the process of welding. After 80 times of iteration, the actual output of the welding system can better track on the desired trajectory and realize the high precision tracking control in the finite interval. It verifies the effectiveness of the proposed method. The better tracking performance can be acquired by ILC in contrast to PID algorithm.

    Design of LPV Fault Tolerant Controller for Wind Turbine Based on Combined Zero-process

    WU Ding-hui, ZHENG Yang, HUANG Xu
    2019, 26(11):  2086-2092. 
    Asbtract ( )  
    Related Articles | Metrics
    A fault tolerant method of combined double-layer convex polyhedron linear parameter varying (LPV) based on the zero processing is proposed in addressing the problem of pitch-angle sensors malfunction. The traditional LPV model is convert to the double-layer LPV model by optimizing its convex polyhedron vertices at first. Then, the combined thinking and zero processing are employed to design each sub-controller of the system, and the final controller is obtained from the combination of these sub-controllers. This approach solves the fault-tolerant control problem of pitch angles malfunction with reducing the linear deviation of LPV model in a concise way, which guarantees the stable operation of the wind turbine.

    The State Estimation and Fault Detection Algorithm Based on Projected Zonotopes

    PAN Jiao, WEN Chuan-bo
    2019, 26(12):  2297-2302. 
    Asbtract ( )  
    Related Articles | Metrics
    A state estimation algorithm based on zonotope and projection operator is proposed for discrete-time uncertain systems. The algorithm updates the state via finding the intersection of the prediction set and  measurement set. A zonotope for the unitary interval is obtained via constructing the projection operator; Plugging the zonotope into the simultaneous equations, the compact set of the guaranteed state estimation is derived for the measurement updation at last. A fault detection algorithm based on the proposed estimation algorithm is derived via detecting whether the set of prediction output contains the values of measurement output. The example has been provided for clarifying the algorithm.
    Method on Nonlinear Adaptive Controller for Maglev Levitation Ball System
    LV Zhi-guo, LONG Zhi-qiang
    2020, 27(1):  127-133. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at the problem of designing adaptive controller for different plants for maglev ball system, a nonlinear adaptive control approach based on combination of feedback linearization and parameter identification is presented. Firstly the maglev ball system mathematical model is formulated by using the theory of state feedback exact linearization. Secondly a nonlinear controller is designed via system state feedback, and the method of controller parameter identification online is presented. The online experiments on MATLAB platform show the system using the presented approach has more advantages than backstepping sliding model control method, which can adaptively suspend different plants in equilibrium position. Furthermore it has ideal steady-state regulation performance.

    Event-triggered Control for Consensus of Linear Uncertain Systems

    KE Ya-wei, PU Nan-nan
    2019, 26(2):  302-307. 
    Asbtract ( )  
    Related Articles | Metrics
    In this paper, a new kind of distributed event-triggered control strategy is proposed for the consensus of general linear uncertain multi-agent systems. By considering the state uncertainty, input uncertainty and external disturbance in the control model, the event-based control algorithm and event-triggered condition are designed. Using Lyapunov stability theory, it is proved that the bounded consensus can be achieved for all agents. Finally, a numerical example is given to verify the theoretical result. The specific structure is as follows: for a class of systems with state uncertainty and input uncertainty, a distributed event-driven control algorithm is designed. Furthermore, for each agent, the algebraic Riccati equation is used to derive the distributed event-driven conditions. It is proven that the asymptotical consensus can be achieved by Lyapunov stability theory. Finally, a class of aircraft systems are taken as an example to demonstrate the effectiveness of the proposed method.
    Improved Multi-model Extended Kalman Filter for Nonlinear systems
    NING Zi-jian, FENG Xiao-liang, WEN Cheng-lin
    2020, 27(02):  342-346. 
    Asbtract ( )  
    Related Articles | Metrics
    A new multi-model extended Kalman filter algorithm is proposed for a kind of nonlinear systems, in which, the state equation includes a linear part and a nonlinear part, the measurement equation is a linear function. Firstly, the multi-model Kalman filter method is improved and named as IMMEKF. Secondly, the original system is divided into a linear part and a non-linear part. Thirdly, in the process of time update, the Kalman filter algorithm is used to predict the state of the linear part, and the improved multi-model extended Kalman filter algorithm is utilized to predict the state of the nonlinear part. Then, in the measurement update process, a sequential updating method is given to correct the predicted value of the linear part and the non-linear part gradually. The final simulation results illustrate the nonlinear filtering property of the two filtering methods.
    Safety Analysis of Railway Signal Systems Based on Extension
    MA Yan-xia, ZHENG Yun-shui, MA Bing, YUE Xiao-xue
    2019, 26(3):  525-531. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to analyze the security risk of the computer interlocking system more accurately and comprehensively, a risk evaluation model for the computer interlocking system is proposed based on the game theory and extenics theory. To achieve a more accurate assessment result, the idea of game theory is used to realize the optimization combination of the subjective weight which is determined by using the G1 method and the objective weight which is determined by using the entropy weight method. Normalizing the classical field matter-element and the evaluating matter-element and using unsymmetrical proximity replacing maximum membership degree principles could effectively solve the problem in the extension method. The analysis results show that the method is suitable for the safety analysis of computer interlocking systems.
    Design and Analyze a Window Cleaning Robot
    CHEN Hai-chu, LI Qiang
    2019, 26(4):  740-745. 
    Asbtract ( )  
    Related Articles | Metrics
    It designed a window cleaning robot (WCR) in this paper. In the bottom of the WCR, it designed two vacuum suckers and connected with a vacuum pump by hoses which exhausts the air in the sucker and creates vacuum in it. Then, negative pressure makes by atmosphere, which can make the WCR adhere to window glass. Two crawler wheels are designed to increase the contact area between the WCR and glass, which can improve the driving force of the WCR when it moves on glass. Also, it designed a negative pressure sensor and connected with the vacuum suckers by hoses, which can realize real-time monitoring the negative pressure of the WCR, and make the control system automatically adjust the PWM control parameters on the vacuum pump motor to change the negative pressure in the vacuum suckers of the WCR and make it adapt different glass with different friction coefficient and move freely. According to the designed structure parameters of the WCR, it set up the simple mechanical model, and then analyzed the negative pressure model, driving model of the WCR. At last, it made the WCR sample and tested the adherence ability and the moving ability of it. The experimental results prove the load capacity of the WCR is over 10kg when it adheres to smooth glass window, and can move freely on different glass with different friction coefficient.
    Under-actuated UUV Depth Controller Design Based on Linear ADRC Technology
    HUANG Jian, SHU Xiao-di
    2019, 26(5):  927-934. 
    Asbtract ( )  
    Related Articles | Metrics
    To improve the depth control quality of Under-actuated unmanned underwater vehicle (UUV) in the complex environment, linear active rejection disturbance control (LADRC) technology is applied to the depth control of Under-actuated UUV. First, linear extended state observer (LESO) is used to estimate the system of unknown "combined interference", and carry on dynamic feedback compensation, to simplify the system to the standard model. Then, based on the standard model the controller is designed. Finally, the controller is modified, by introducing a saturation limiter and dead zone. Comparing with the cascade feedback controller, linear ADRC has better dynamic and static characteristics and robustness in the situation of constant interference and first-order high frequency wave force interference and low frequency sinusoidal interference. Compared with the traditional nonlinear active rejection disturbance controller (NADRC), the LADRC has the advantages of less parameters and easy engineering realization under the premise of ensuring the control performance.
    Online failure identification method for power equipment based on metering automation and integration platform
    TAN Yu-hang, ZHANG Zhen-tao, YUAN Ling, LIANG Kang-you
    2019, 26(6):  1133-1137. 
    Asbtract ( )  
    Related Articles | Metrics
    Based on metering automation and integration platform, the online failure-identification method for power equipment of some special variable users is designed in order to solve the problem of quick failure-identification in the value-added service mode provided for those users. In the beginning, the time-series auto regression model for the device state parameters was set up, then the time-series including the device state values was quantized as the inputting ones of the system by self-organizing maps. The learning samples of the least square support vector machines model were built by using process input values in the sliding time window. The differences between the calculating regression results and measuring values of the feature vector were set as the observed ones. The background model of the system configured Background model of multidimensional observation value distribution system was fit by the Gaussian mixture model, in which the failure index was calculated by the matching degree between the individual observation and the background model to achieve the real-time identification of the equipment failure. The experimental results show that this method is able to predict failures online quickly and accurately.
    Detection of Navel Orange Diseases Based on Watershed Edge Segmentation FSONN
    GU Si-si, LI Wen, HUANG Li-shao, CHEN Wei
    2019, 26(7):  1353-1359. 
    Asbtract ( )  
    Related Articles | Metrics
     In order to further improve the performance of detection and recognition algorithm for navel orange disease, a kind of fuzzy detection method based on the watershed segmented edge self-organizing neural network(FSONN) is proposed. Firstly, the watershed segmentation algorithm was used to realize the effective extraction of the boundary of navel orange, and used the expression of red, green components in the disease region to characterize the disease of navel orange, used the fractal dimension of the navel orange disease to be the shape expression, and used the above features as the input of neural network algorithm to construct an automatic detection model of navel orange disease. Secondly, the fuzzy self-organizing neural network algorithm was proposed to realize the automatic model parameters and structure identification based on the self-organizing clustering method; Finally, through the experiment on the MackeyGLass approximation of nonlinear sequences in the proposed algorithm, the performance advantages can be verified, and applies it in navel orange disease detection, the experimental results show that the correct rate of 4 kinds of navel orange disease detection by proposed algorithm can reach more than 90%, which can meet the needs of practical applications.
    The Improved Particle Swarm Optimization Algorithm Based on PID Control Theory
    YANG Xiao, WANG Guo-zhu
    2019, 26(8):  1497-1502. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to solve the problem of the particle swarm algorithm in slow search speed and easy to fall into local optimum. This thesis analyzed the iterative formula of the algorithm based on PID control theory, revealed that the speed update mechanism of the algorithm essentially adopts a proportional integral (PI) approach, and improved the iterative formula of particle swarm algorithm based on the theory of the PID control mechanism. In order to verify the effectiveness of the proposed strategy, It achieved the function of the algorithm by using MATLAB programming, and made a detailed comparison with the standard particle swarm algorithm by the benchmark test function. The results showed that the convergence rate of the improved particle swarm optimization algorithm is improved obviously, and the algorithm can avoid falling into local optimum.

    The Safety Analysis of Carrier-based Aircraft Landing Based on Baseline Statistical Methods

    YUAN Xin, ZHANG Wen, SUN Ye, LIU Zhi-lin
    2019, 26(9):  1733-1737. 
    Asbtract ( )  
    Related Articles | Metrics
    The carrier aircraft safe landing is very difficult and dangerous .So it is very important and necessary to research on the aircraft carrier landing safety analysis and assessment. The aircraft carrier landing simulation platform is used to obtain a large number of sample data. Statistical methods are used for analysis and processing of these data, and the baseline of standard operating procedures are formed. The whole aircraft carrier landing process is divided into important positions of each stage. By using baseline comparative leading indicators methods, the leading indicators of each position are compared and analyzed for aircraft carrier landing process to obtain evaluation of carrier pilots landing performances. The simulation results verify the effectiveness of this method.
    The Tracking Control of Unmanned Underwater Vehicles Based on Model Predictive Control 
    MEI Man, ZHU Da-qi, GAN Wen-yang, JIANG Xiao-di
    2019, 26(10):  1917-1924. 
    Asbtract ( )  
    Related Articles | Metrics
    In terms of the tracking problem of unmanned underwater vehicles (UUV) in two-dimension, a new approach of the tracking control algorithm is investigated by analyzing and building the two-dimension kinematic model of UUV in this paper, that is model predictive control. The model predictive control is employed based on the linear error model, the optimization problem of minimizing the objective function is transformed to a quadratic programming problem, which makes it effective to realize the tracking control and avoid the speed jump problem under the condition of satisfying the control constraints. The experimental results show the efficiency in terms of the trajectory tracking control problem for UUV, when compared with the method of backstepping.

     The Selection Method of Network Public Opinion Prediction Based on Fuzzy Information Aggregation

    QIN Li-na
    2019, 26(11):  2093-2098. 
    Asbtract ( )  
    Related Articles | Metrics

     For the network public opinion prediction model selection problems in which the attribute values are in the form of hesitant fuzzy information and the input arguments are associated with each other, a novel hesitant fuzzy Heronian geometric mean (HFHGM) operator is proposed on the basis of Archimedean norm and Heronian geometric mean, whose properties are studied in detail. Then, some special cases of the HFHGM operator are discussed and the hesitant fuzzy weighted Heronian geometric mean (HFWHGM) operator is introduced. In addition, a new hesitant fuzzy multi-attribute decision making method based on HFWHGM operator is developed, which can capture the interrelationships among the input arguments and enable decision maker to select different parameters to make decision in accordance with their own risk preferences attitude. Finally, a numerical example about the network public opinion prediction model selection is provided to illustrate the effectiveness of the developed method.

    Micro Electric Net Petri Model Based on the Structure of I Type Synchronous Decomposition

    ZHU Ming-xing, SUN Zheng-lai, LIU Wen-ye, WU Zhong-chao, XU Fei, YE Hai-feng, ZHAO Dai-ping
    2019, 26(12):  2303-2308. 
    Asbtract ( )  
    Related Articles | Metrics

    In order to solve the problem of poor synchronization, discrete and continuous events coexist, a micro grid Petri monitoring model based on the structure of I type synchronous decomposition is proposed to improve the accuracy of the model construction of micro grid. Firstly, the research for Petri net system model of micro grid system was conducted, and the Petri network based main network model, micro source energy, storage system model, the standby power supply model and load model were built; Secondly, in order to improve the performance of Petri network model, the network structure decomposition method was used to construct Petri model based on the structure of I type synchronous decomposition, Petri complex control was multiple sets of simplified local subnet control problems; Finally, the effectiveness of the proposed model is verified based on micro grid Stateflow monitoring simulation system.

    PSO-based Weft Insertion System for Three-dimensional Tubular Loom
    ZHOU Qi-hong, OU Si-fan, LI Qing-qing, SUN Zhi-hong, CHEN Ge
    2020, 27(1):  134-137. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to meet the requirements of the strict motion relationship between the weft insertion mechanism and the opening mechanism of the three-dimensional tubular loom, a set of digital control adaptive weft insertion system was designed. The system drives mechanism of weft insertion motion of the shuttle, with the aid of a speed reducing mechanism based on servo motor and a synchronous and gear column driving mechanism. Encoder is used to get real-time angle, and the micro controller STM32F407 is the main control chip of the system. The adaptive control algorithm, with IATE accuracy standard and particle swarm optimization algorithm, can realize the parameter self-turning function. The system has been proved to meet the requirements of the synchronous control of the weft insertion mechanism and the opening mechanism of the three-dimensional tubular loom, and it can also satisfy the requirements of the three-dimensional tubular fabric weaving.

    Multi-objective Layout Optimization of Oil-gas Pipeline Network Based on NSGA- = 2 \* ROMAN \* MERGEFORMAT II

    LIU Qiang, MAO Li
    2019, 26(2):  308-313. 
    Asbtract ( )  
    Related Articles | Metrics
    This paper presents a multi-objective layout optimization method for the oil-gas pipeline network based on NSGA- = 2 \* ROMAN \* MERGEFORMAT II. Pipeline construction costs and gas collecting station construction costs are formulated as major objectives, and the model of multi-objective optimization in oil and gas pipeline network layout planning is established. By using non-dominated sorting genetic algorithm- = 2 \* ROMAN \* MERGEFORMAT II (NSGA- = 2 \* ROMAN \* MERGEFORMAT II) to solve the multi-objective problem, polygon is used to describe the obstacles, and obstacle avoidance is handled using the visual graph method. The proposed method considers multi-objective optimization of the oil-gas pipeline network and obstacle avoidance constraints, so it has good general theory and practical application value. Finally, a numerical example of oil and gas pipeline network is provided to verify the feasibility of the proposed method.
    Attitude Synchronization Control of Multiple Unmanned Aerial Vehicles with Time-varying Communication Topological Structures
    REN Bin, LIN Da, TAN Fu-xiao, LIU De-rong
    2020, 27(02):  347-354. 
    Asbtract ( )  
    Related Articles | Metrics
    Based on the communication topology from algebraic graph theory, the consensus protocol and coordination control of multiple unmanned aerial vehicles have always been a hot research topic in the field of automatic control. Since the attitude dynamics model of unmanned aerial vehicles is an Euler quaternion, the design of attitude synchronization controller of multiple unmanned aerial vehicles is very difficult to perform. Under time-varying communication topology, in this paper, the attitude synchronization control problem of multiple unmanned aerial vehicles is investigated. Furthermore, the implementation conditions of attitude synchronization are analyzed and the synchronization control algorithm is also designed. In the case of undirected graph and time-varying communication topology, it is proved that the attitude control algorithm can not only realize the attitude synchronization of multiple unmanned aerial vehicles, but also can guarantee the final angular velocity converge to zero. Under different circumstances of fixed switching cycles, time-varying, fast time-varying, slower time-varying, and isolated point in communication topology, based on the above results, the attitude synchronization control problems of multiple unmanned aerial vehicles are compared by computer simulation, and the effectiveness and the robustness of the proposed attitude synchronization control algorithm are also verified.
    Study on Mechanism Modeling and Dynamic Characteristic Analysis for Alkali Recovery Boiler
    LI Yan, WEI Fei, WANG Su-fang, FENG Yin-an
    2019, 26(3):  532-541. 
    Asbtract ( )  
    Related Articles | Metrics
    The 130 tds/d alkali recovery boiler is taken as the research object, the nonlinear relationship and the coupling relationship between boiler temperature, oxygen content, furnace pressure and the boiler black liquor flow, supplying air, air exhaust is considered, the principle of material balance and energy balance is used, and a control oriented dynamic mathematical model of the alkali recovery combustion process is established. The dynamic characteristics of the model are analyzed, results show that the model is consistent with the actual production, which can reflect the field operation of the alkali recovery boiler. The relative gain matrix is used to analyze the correlation degree of the system, and the three-input-three-output system can be decomposed to a two-in-two-out coupling system and a SISO control system, which can simplify the design of the alkali recovery boiler control system, providing a theoretical basis for the control strategy and control scheme of the alkali recovery boiler.
    Process Fault Diagnosis Using Kernel Canonical RF
    CAO Yu-ping, LU Xiao, TIAN Xue-min, DENG Xiao-gang
    2019, 26(4):  746-751. 
    Asbtract ( )  
    Related Articles | Metrics
    Traditional rotation forest based on principal component analysis does not consider time series correlation of features. Therefore, a fault diagnosis method based on kernel canonical rotation forest is proposed to improve fault diagnosis accuracy in nonlinear dynamic processes. For the proposed method, random forest features are projected to the high dimension linear reproducing kernel Hilbert space by using unknown nonlinear mapping. Canonical variate analysis is used to extract dynamic correlation information, and to produce irrelevant features. Kernel function is used to solve the unknown nonlinear mapping problem. In order to avoid kernel matrix singular problems in traditional kernel canonical variate analysis, canonical variables are extracted in kernel principal space, and used to train decision trees. The proposed method takes nonlinear correlation and dynamic correlation of random forest features into account. Meanwhile, the difference between decision trees is increased, which is helpful to improve the accuracy of fault diagnosis. The effectiveness of the proposed method is demonstrated through a case study of the Tennessee Eastman process.
    Target Tracking Algorithm with Double-type Agents Based on Flocking Control
    WANG Shuai-lei, ZHANG Jin-chun, CAO Biao, CONG Kai
    2019, 26(5):  935-940. 
    Asbtract ( )  
    Related Articles | Metrics
    A target tracking algorithm with double-type agents based on flocking control for a system consisting of two kinds of agents is proposed here, and this algorithm can make different agents reach a specific leading-following state and all the agents track a moving target. Firstly, design a system consisting of two types of agents based on the classical flocking control algorithm, analyze the difference between the two types of agents, introduce the tracking relation and the interaction force. Secondly, analyze the forces and design a repulsive potential function, and builds control input for the agents respectively, which can make the agents keep a same velocity with the target and track it stably. Finally, the algorithm is analyzed by Lyapunov stability method and theoretical proof is presented. And the effectiveness of this algorithm is verified by simulation.
    Dynamic Robust Compensation Control for Electro-hydraulic Proportional Differential Variable-pitch of Wind Turbines
    WANG Hui , YANG Qiu-shi
    2019, 26(6):  1138-1144. 
    Asbtract ( )  
    Related Articles | Metrics
    To overcome the impact of randomness of wind speed on dynamic characteristics of wind turbines system, a dynamic robust control method is used to compensate the uncertainty and external disturbance for the electro-hydraulic proportional differential variable-pitch system of wind turbines. Primarily, a mathematical model for wind turbines system was constructed in accordance with the process of electro-hydraulic proportional differential feathering. On this basis, a dynamic robust control system for wind turbines was proposed combined with a dynamic robust compensation controller. Furthermore, a simulation model of the given control system in the process of feathering was established by utilizing MATLAB/Simulink module. Under the condition of different wind speed signals, simulated and analyzed the control system in two cases that it contained and didn’t contain dynamic robust compensation controller. Finally, the response characteristic curves corresponded with given wind speed signals can be obtained. The simulation results indicate that the dynamic response of the proposed control system, which contains a dynamic robust compensation controller, is little influenced by different wind speed signals. Thus, under the application of dynamic robust compensation controller, the stability and robustness for variable-pitch control of the wind turbines are improved.
    Sampled-data Model of Nonlinear Mass-spring-damper Mechanical Vibration Systems with Relative Degrees Two
    XU Ming-can, ZENG Cheng
    2019, 26(7):  1360-1364. 
    Asbtract ( )  
    Related Articles | Metrics
    The approximate sampled-data models and discretization properties are derived for nonlinear multivariable mass-spring-damper mechanical vibration systems when the corresponding relative degrees of continuous plant are both two. The proposed sampled-data models use a more sophisticated derivative approximation than the simple Euler approach, and the local truncation error and global truncation error are also represented, respectively. An insightful interpretation of the given sampled-data models can be made in terms of an explicit characterization of nonlinear sampling zero dynamics which have no continuous-time counterpart. More importantly, nonlinear discrete-time controller design is also represented based on the above sampled-data model and zero dynamics. The ideas presented here generalize well-known results from the linear case to nonlinear plants. Finally, we also explore the implications of these results in nonlinear system identification.
    The Research on the Selection of Transportation Logistics for Car Enterprises Based on the Fuzzy Bi-directional Projection
    FANG Ming-qing
    2019, 26(8):  1599-1604. 
    Asbtract ( )  
    Related Articles | Metrics
    Under the interval-valued intuitionistic fuzzy information environment, with respect to the multiple attribute group decision making problem in which the attribute weights are completely unknown, based on the bi-direction projection weights model, a novel multi-attribute group decision making (MAGDM) method is developed. First, the idea alternative and critical alternative are obtained in accordance with collection decision making matrix provided by decision makers, and the correlation coefficient and projection length are determined on the basis of projection formula. Then, with the principle of maximization and minimization of objective functions, a multi-objective optimization model is constructed to get the attribute weights. Finally, the bi-direction projection optimization model of attribute weight vector is investigated, the ranking order based on the improved VIKOR and TOPSIS is obtained, and a numerical example about the logistics transportation partner selection is provided to illustrate the effectiveness of the developed method.
    Control Strategy of Hybrid Multi-terminal HVDC Transmission System
    HUANG Zhi-da, HUANG Qing-song
    2019, 26(9):  1738-1744. 
    Asbtract ( )  
    Related Articles | Metrics
    A hybrid multi-terminal HVDC transmission system is established. The rectifier side of the system is two sets of twelve pulsating line commutated converter (LCC) in series, t the inverter side is double-ended three-phase two-level voltage source converter (VSC).. On the basis of expounding its topology and working principle, the overall control strategy of system is designed and analyzed. The steady-state operation and transient fault process of the system are simulated by the electromagnetic transient simulation software PSCAD/EMTDC. The simulation results verify the effectiveness of the hybrid multi-terminal HVDC transmission system control strategy.
    Multi-Model Fusion Soft Sensor Modeling Using FCM-ABC-MKRVM
    ZHANG Hong-de, XIA Lu-yue, LIU Yong, PAN Hai-tian
    2019, 26(10):  1925-1931. 
    Asbtract ( )  
    Related Articles | Metrics
    Many chemical processes have the characteristics of strong nonlinearity, complex mechanism and multiple operating conditions. Aiming at the problem that traditional soft sensor model can’t fully describe the process characteristics, which leads to the low prediction accuracy, a multi-model fusion soft sensor modeling method based on FCM-ABC-MKRVM is proposed. Firstly, the fuzzy C-means (FCM) clustering algorithm was used to divide the training samples into several subclasses and the clustering centers of each subclass were determined. Then, the multi-kernel relevance vector machine (MKRVM) sub-models were established by training each subclass samples. The kernel parameter and weight factor were optimized by artificial bee colony (ABC) algorithm. In the stage of the model prediction, the membership values between the test samples and the cluster centers were calculated as the weight coefficients of the output values of sub models. The final prediction output was obtained by the multi-model fusion. The proposed modeling method was applied to develop polypropylene melt index soft sensor. The result shows that the melt index soft sensor model based on FCM-ABC-MKRVM has better predicting accuracy compared with the MKRVM model and the ABC-MKRVM model. The proposed modeling method could provide guidance for online predicting of the quality index of chemical process under complex multi-operating modes.

    The Stability of Coupled Four Rotor Unmanned Aerial Vehicle based on ADRC Controller

    SHI Yan-xia, QIAO Jia, XUE Long
    2019, 26(11):  2099-2103. 
    Asbtract ( )  
    Related Articles | Metrics
    It is difficult to establish a system model for the internal uncertainty factors in the four rotor UAV system, and strong coupling and external environment interference increase the difficulty of vehicle control, a four rotor UAV control scheme based on active disturbance rejection control(ADRC) is proposed. By analyzing the mathematical model of the four rotor UAV system, using the ADRC strategy, the coupling between each loop, the internal uncertainties and external disturbances are regarded as the expansion state, the disturbance is suppressed by feedback compensation to make the system approximate to the series integrator type, and then which is compensated by nonlinear state feedback controller. Compared with the traditional PID simulation data, the ADRC has better control effect on the four rotor UAV system, and the control strategy has better robustness and dynamic performance.

    Estimation of the State of Charge for Lithium Battery Based on D’STA - RBF Neural Network Algorithm

    YANG Chun-hua, LI Xue-peng, CHEN Ning, ZHOU Xiao-jun
    2019, 26(12):  2235-2240. 
    Asbtract ( )  
    Related Articles | Metrics
    Concerning the problem of the prediction accuracy of the State of Charge (SOC) of lithium-ion battery, a method of SOC estimation for lithium-ion batteries based on a Radial Basis Function (RBF) neural network optimized by a dual state transfer algorithm is proposed. The number of hidden layers in RBF neural network is determined by the K-means algorithm and the K-means clustering algorithm is optimized by state transition algorithm (STA), so that the network structure of RBF neural network is determined reasonably. Based on the optimal network structure, the parameters of network, including the center, width and connection weight, are adjusted by STA. Then using the trained RBF neural network to estimate the SOC of lithium-ion battery. The effectiveness of the proposed method is compared with the ampere-hour integral method and a back propagation (BP) neural network. The results show that the method is superior to other methods.
    Design of Adaptive Sliding Mode Control for Four-rotor Aircraft
    Gu xun, Zheng Ya-li, Chen Yu-qing
    2020, 27(1):  138-142. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at the modeling error and external disturbance uncertainty of four-rotor aircraft attitude model, a nonlinear controller based on adaptive sliding mode is proposed. The parameter adaptive control method is used to approximate the modeling error term in the system, and the sliding mode control method can cancel out the system modeling error and the external uncertain disturbance term. The Lyapunov stability method is used to prove that the designed controller can achieve global asymptotic stability. Then, the validity of the control method proposed in this paper is verified by the real flight test, which can realize the attitude stabilization control of small four-rotor aircraft, and show that anti-disturbance performance is better than traditional PID control.

    An Active Learning Algorithm Based on Imbalanced Datasets

    ZHAO Xiao-qiang, LIU Meng-yi
    2019, 26(2):  314-319. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at the problems of noise data and low classification accuracy in the classification process of imbalanced datasets, an active learning SVM classification algorithm based on improved SMOTE is proposed. This algorithm uses the attribution values of the minority class samples for training the sample set to choose and control the number of synthetic minority class samples by the majority vote method. According to the distance formula, the hyperplane is determined. The same number of majority class samples which are closest to the classification hyperplane are selected to form a balanced sample dataset. Support vector machine (SVM) is used to classify and obtain an optimal classifier. Then active learning is used to the imbalanced dataset which removes the training samples to circulate classification until samples of the imbalanced dataset is null by using the optimal classifier. Using UCI data, the experimental results show that the proposed algorithm can effectively reduce noise influence for data classification and improve the classification accuracy of the imbalanced dataset.
    Multi-model Switching DMC-PID Cascade Predictive Control for SCR Flue Gas Denitrification System#br#
    HOU Peng-fei, JIA Xin-chun, BAI Jian-yun, WANG Qi
    2020, 27(02):  355-360. 
    Asbtract ( )  
    Related Articles | Metrics
    In view of the non-linearity, time-varying and large delay characteristics of SCR flue gas denitrification system, a multi-model switching DMC-PID cascade predictive control method for variable conditions operation is proposed under the background of coal-fired units participating in deep peak shaving. Firstly, the local linear model of SCR denitrification system under different working conditions is established by using system identification method. Secondly, the parameters of DMC-PID controller are designed according to the principle of quadratic optimal control. Finally, the switching conditions are designed according to the unit load instructions, and the DMC-PID cascade predictive control of denitrification system under variable conditions is realized by using multi-mode switching control method. The results show that compared with DMC-PID cascade predictive control without switching control and cascade PID multi-mode switching control with switching control, the multi-mode switching DMC-PID cascade predictive control designed in this paper has the advantages of small output fluctuation, small overshoot, short adjustment time, rapid response, strong anti-interference ability and good robustness under variable operating conditions, and is suitable for industrial process control with non-linearity, time-varying, large delay and variable operating conditions.
    The Pricing Strategy of Information Consumption Goods of Duopoly Enterprises
    ZHANG Ya-ming, SU Yan-yuan
    2019, 26(3):  542-548. 
    Asbtract ( )  
    Related Articles | Metrics
    By introducing the consumers’ loyalty and the network externality which both have great effects on the value of the information consumption goods into the consumer utility function, this paper improves the traditional Hotelling pricing model, discusses the equilibrium strategies between the uniform pricing and discriminatory pricing. The results show that if the two network externalities tend to be symmetric, both enterprises would choose the discriminatory pricing, and the strategy selection is not sensitive to customers’ loyalty; if the two network externalities tend to be asymmetric, the equilibrium strategies would change from uniform pricing to discriminatory pricing as the premium that consumers are willing to pay in order to keep their loyalty increases Besides, with the increase of the difference between two network externalities, the sensitivity of the strategy selection on customers’ loyalty becomes decreases.
    Prediction of Aircraft Fuel Flow Based on QAR Data
    CHEN Cong, SHI Li-zhong, GAO Jie, DONG Shi-yao, CAO Jin-jin
    2019, 26(4):  752-758. 
    Asbtract ( )  
    Related Articles | Metrics
    At present, most of the domestic service B737NG aircraft using CFM56-7 type engine. As the research object, by decoding the vast data of quick access recorder (QAR), the denoising method with stationary wavelet Rigorous SURE, analyzing the engine speed, N1 speed, N2 speed, exhaust gas temperature (EGT)and other parameters, processing linear or nonlinear regression analysis, combined with the flight phase rational division and modeling, analysis of the main performance parameters and aircraft fuel flow (FF) relationship, full range of the FF prediction model is established. Through MATLAB-Simulink simulation analysis, 5 representative cases of the long flight, short-middle flight, take off-go around flight and complex flight are selected, and errors of the FF prediction model and the actual flow are compared to prove that the model is reasonable and universal.
    UAV Video Stabilization Using Homography Revised P-KLT
    WANG Jie, WANG Wei-bin, YU Li, XIE Bei-min, YIN Wei-wei
    2019, 26(5):  941-946. 
    Asbtract ( )  
    Related Articles | Metrics
    There are inevitable shakes in videos taken by handheld devices and UAVs, which reduce the effect of video viewing and post-processing. In the video stabilization technology, similar matrix transformation is often used to perform inter-frame correction to have a real time processing. But the compensation effect for three-dimensional motion is poor to use similar matrix transformation. On the other hand, the homography matrix transformation that can represent three-dimensional motion, can not meet the real time requirements. To solve this problem, a video stabilization technique based on homography revised P-KLT is proposed. This algorithm is based on the optical flow tracking theory and realizes real-time parameter tracking calculation for the homography matrix transformation. A distortion correction algorithm based on vertex filtering is proposed to meet the requirements of 3D motion video real-time image stabilization. The experimental results show that the video images processed by this algorithm are stable and natural, especially for videos with motion blur. 
    Researching on the Electromagnetism-like Mechanism Algorithm for Solving LBFFSP
    HAN Zhong-hua, SUN Yue, LIN Shuo
    2019, 26(6):  1145-1152. 
    Asbtract ( )  
    Related Articles | Metrics
    To solve the limited-buffer flexible flow shop scheduling problem (LBFFSP), the LBFFSP’s mathematical model is established, and an improved electromagnetism-like mechanism algorithm (IEM) is proposed as the global optimizing algorithm. The random search is used in the local search strategy of standard electromagnetism algorithm, and the searching range of EM algorithm is small and it is easy to fall into the local extremum. So the idea of simulated annealing is introduced to accept the solution which makes the objective function value worse with a certain probability, which can enlarge the searching range of the algorithm, and increases the diversity of population particles, and effectively avoids the algorithm getting into the local optimal solution in the iterative search process. In addition, in order to further improve the efficiency of the algorithm for searching the optimal solution, the initial population establishment method based on optimization objective is designed to improve the quality of the initial solution of the initial population. Finally, the effectiveness of the IEM algorithm in solving the limited-buffer flexible flow shop scheduling problems is verified by comparing with SAEM algorithm and standard EM algorithm through examples tests.
    Optimization Technology of Capacity Control Method for Reciprocating Compressor
    LIU Wen-hua, JIANG Zhi-nong, ZHANG Tian-yu, WANG Yao, ZHANG Jin-jie
    2019, 26(7):  1365-1371. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to meet the demand for capacity control of reciprocating compressors, the mechanism modeling of the relationship between discharge pressure and flow is established. Then the variable pairs with smaller coupling correlation degree are selected by calculating the steady-state relative gain of the model. The distributed PI control strategy is used to verify the matching relationship between the mechanism model and the actual system. Meanwhile, the model identification method is used to translate the mechanism model into transfer function matrix. And for the first time, the transfer function matrix is used to design the internal model controller of the paired main loop to replace the traditional PI controller, which reduces the difficulty of parameter tuning. Simulation and experimental results show that the proposed method achieves good target tracking performance and robustness, and optimizes the control effect of the system.
    Online Prediction of Short-term Wind Speed and Power Generation Based on Phase Space Reconstruction
    HAN Ya-jun, LI Tai-fu
    2019, 26(8):  1503-1508. 
    Asbtract ( )  
    Related Articles | Metrics
    Wind power is characterized by intermittent, randomness, volatility and accurate prediction with little possibility. The large capacity wind power will bring serious challenges to the safety and stability of power system. According to the chaotic characteristic of wind speed, a new short-term prediction method of phase space reconstruction theory is put forward. The optimal delay time τ and embedding dimension m of the wind speed must be determined firstly. Then match m with τ, and find a best matching sample to reconstruct the phase space, finally using the BP neural network to forecast the short-term wind speed. By simulating the measured data of a wind power plant in Wulong region of Chongqing, the effectiveness and feasibility of the method is proved, and the accuracy of short-term power generation prediction is improved. It is also of great significance for the operation of grid connected wind power generation system.
    Capacitor Voltage Balancing Control of Modular Multilevel Converter Based on Circulation Current Suppression Strategy
    MA Xiu-juan, TENG Jia-yi, YAO Tong
    2019, 26(9):  1745-1750. 
    Asbtract ( )  
    Related Articles | Metrics
    There are many advantages for modular multilevel converter (MMC), such as modular structure, scalability and reduced harmonics, which makes it become a potential converter technology for high voltage direct current (HVDC) transmission system. The basic topology structure and working principle are introduced, capacitor voltage fluctuation and circulation current are analyzed, and point out the necessity of controlling. Capacitor voltage balancing control based on circulation current suppression strategy are applied to keep voltage stability of sub-module(SM) capacitor and suppress circulation current. Circulation current suppression controller based on low pass filter and quasi-proportional resonant controller is designed and added to additional capacitor voltage balancing control strategy. The effectiveness and feasibility of the proposed method is proved by Matlab/Simulink, the simulation results show that the fluctuation of capacitor voltages as well as the circulating current can be confined into acceptable range.

    Research on Learning Algorithm of Neural Networks Based on Improved Fading Unscented Kalman Filter

    YANG Yi, GAO Yi, LIU Hai-long
    2019, 26(10):  1932-1938. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at the defects in the training process of BP neural networks, a novel learning algorithm of neural networks is designed based on the improved fading unscented Kalman filtering in this paper. In this algorithm, the filter gain matrix in the algorithm of UKFNN is adjusted by introducing the adaptive factor, which is calculated by an improved calculation method. Therefore, the influence of sample noise on the weights updating is limited and thus the training accuracy is improved. Meanwhile, the calculation burden of fading factor could be simplified by the improved calculation method. Finally, the proposed algorithm is applied to INS/GPS integrated navigation system for establishing an error estimation model. The experiment results demonstrate that the fitting precision of the prediction model could be advanced by the proposed algorithm, and the adaptive ability for noise samples could be improved effectively, as well as has better application prospects.

    A Circular Target Localization Method from Degraded Images

    WU Jian, FU Lian-lian
    2019, 26(11):  2104-2108. 
    Asbtract ( )  
    Related Articles | Metrics
    Circular target localization from a digital image is an important task in computer vision. In this paper, a new algorithm to locate circular objects from degraded gray scale images is proposed. A new type of difference named contour difference is used in this method to detect circular object. The contour difference is calculated directly on the image space, not on the edge map. This procedure needs neither any pre-processing, such as deblurring and denoising, nor edge detection on the input picture. By the new operator, the task of circular target localization becomes a peak searching problem in the space of contour difference data. The experiments show that the proposed method outperforms the circular Hough transform and the recent EDCircles methods on the accuracy in the degraded background, and it is robust to noise and blurs.

    Time Delay Aanlysis for Supercavitating Vehicles

    PANG Ai-ping, HE Zhen, CHAO Fan, YANG Jing, WANG Guang-xiong
    2019, 26(12):  2241-2245. 
    Asbtract ( )  
    Related Articles | Metrics
    The underwater vehicles traveling inside a cavity, enable to reduce the drag and increase the speed.  In the course of operation, the tail of vehicle into contact with the cavity, as a result there is also a planing force acting back on the tail. The time delay effect of the cavity may affect the calculation of the planing force. It is compared in the paper the impact of the delay on the steady-state performance of supercavitating vehicles. And the result show that the time delay cannot change qualitatively the performance of supercavitating vehicles, and the time-delay model of the planing force can be used to simplify the calculation, and the time-delay model can be used for simulation and verification.
    Rotor Position Detection of Permanent Magnet Synchronous Motor Based on Pulsating High Frequency Voltage Injection
    CHAI Jun, JIANG Yan-yu, PENG Yan
    2020, 27(1):  143-147. 
    Asbtract ( )  
    Related Articles | Metrics
    The rotor position detection accuracy of permanent magnet synchronous motor directly determines whether the motor can start smoothly. In order to improve the accuracy of rotor position detection, a rotor position detection method for permanent magnet synchronous motor based on pulsating high frequency voltage injection is proposed. The high frequency voltage signal is injected into the stator windings of permanent magnet synchronous motor, and the rotor initial position is detected by the saturation degree of the magnetic circuit of the   axes of the motor. Experimental results show that the proposed method has high rotor position detection accuracy and it is suitable for sensorless start and low speed state operation of permanent magnet synchronous motor.

    Determination Method for Depth of CDBN Based on Reconstruction Error

    WANG Gong-ming, LI Wen-jing, QIAO Jun-fei, SHEN Zhao-xu
    2019, 26(2):  320-326. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to determine the number of hidden layers in continuous deep belief network (CDBN), a determination method for the depth of CDBN based on the reconstruction error is proposed. CDBN is composed of multiple continuous restricted Boltzmann machines (CRBM). By analyzing the relevance between the reconstruction error and the network energy, and setting the threshold of the reconstruction error, the decision mechanism for the depth is designed to realize self-organizing adjustment for the depth of CDBN. The experiments show that the determination method for the depth of CDBN based on the reconstruction error can determine the optimal depth of CDBN and improve the efficiency of decision depth for CDBN.
    Energy Storage Capacity Optimization Considering the Uncertainty of Islanding Micro Grid
    GAO Min, LU Huai-wei, QIAO Yao, ZOU Wen-jie
    2020, 27(02):  361-367. 
    Asbtract ( )  
    Related Articles | Metrics
    The reasonable planning of energy storage capacity is carried out from the point of view of stabilizing the random fluctuation of new energy output, and the joint probability model of new energy storage system is used to describe the output of micro power supply. A method of probabilistic power flow calculation based on improved sample ranking method is proposed to simplify the correlation control method of multi input random variables of traditional stochastic power flow. In order to reduce the system active power loss, reduce the probability of node voltage exceeding the limit, and consider the operation cost of energy storage device, a multi-objective optimization model is constructed, and the particle swarm optimization algorithm combined with chaotic optimization and linear decreasing inertia weight is used to solve the problem. Finally, an example analysis is carried out in Matlab, and the results show that the stochastic power flow method combined with the joint probabilistic model can effectively solve the multi-objective optimization model, and the system uncertainty is restrained under the constraint condition.
    A Preference Multi-objective Particle Swarm Optimization Algorithm by Hybrid Guidance
    2019, 26(3):  549-554. 
    Asbtract ( )  
    Related Articles | Metrics
    By hybrid guidance, a preference multi-objective particle swarm optimization algorithm (HG-MOPSO) which combines the notion of reference points with reference regions is proposed to obtain the optimal effective set in preference regions. In the process of moving reference points, the algorithm dynamically adjusts reference regions to increase the selection pressure and control preference region whose centre is the reference point. Through the improvement of the option modes of gBest of PSO algorithm by spherical sector dominance (ss-dominance) proposed in this paper, the search for Pareto optimal set of multi-objective optimization problems is implemented. Simulation results show that the proposed algorithm is effective.
    Study on Early-warning of Coal and Gas Outburst Based on Wavelet Packet Entropy and Data Fusion
    TU Nai-wei, YAN Xin
    2019, 26(4):  759-764. 
    Asbtract ( )  
    Related Articles | Metrics
    By analyzing gas concentration change before coal and gas outburst, an early-warning method based on wavelet packet entropy and data fusion was proposed. The data fusion method based on the arithmetic mean and batch estimation is used to deal with the collected multi-sensor gas data so as to improve the precision and reliability of these data. The wavelet packet entropy feature is used to quantize the disordered degree of gas concentration change. An early-warning model for coal and gas outburst based on the wavelet packet entropy feature is used to carry out real-time early-warning. A selection method of the wavelet packet decomposition level based on restructure signal energy was given to scientifically obtain the wavelet packet decomposition level. The proposed method was validated using practical measured time-series data. The simulation example shows that the proposed method can monitor the risk for coal and gas outburst in the working face when the gas concentration change is abnormal before coal and gas outburst.
    Probabilistic Model Template-Based License Plate Localization Method
    WANG Han, SHI Quan, Xu Zhi-huo, WEI Ming, SHAO Ye-qin
    2019, 26(5):  947-951. 
    Asbtract ( )  
    Related Articles | Metrics
    Under complex environment it is difficult to achieve high performance of vehicle license plate localization. A template probability model-based approach is proposed. There are two stages in the proposed method: candidate generation and probabilistic verification. In the first stage, spatial distribution of detected feature points is combined with color information to generate possible candidate region of vehicle license plate; in the second stage, the structure and geometric of standard vehicle license are employed to construct similarity measure probability function. Then the localization of vehicle license plate is detected by extracting maximum similarity measure probability from candidate region. Experimental result shows high performance of the proposed method, such as license plate successful detection rate beyond 96.2 % and miss rate less 3.8%. A novel Chinese license plate localization algorithm was proposed here, which shows low complexity, but high accuracy and practicability. So that it can be applied to license plate recognition.
    Design of the Self-adaptive Filter for Nanometer Positioning Control System
    HOU Jing, LIU Tao, LIU Jin-xin, HAN Zi-yang
    2019, 26(6):  1153-1157. 
    Asbtract ( )  
    Related Articles | Metrics
    In nanometer positioning control system, the control precision is nanoscale. The type and the algorithm of digital filter are the important factors to ensure the positional accuracy. But currently, the filter used in the nanometer positioning system is adopted traditional band stop filter with fixed parameters. When the nano position control system moves or the load is changed, the noise characteristics will change, and then the conventional fixed constant filter cannot effectively eliminate system noise. In order to resolve the problem an adaptive adjustment method of band stop filter which combined culture algorithm and case based reasoning is proposed. The experimental results prove that the proposed filter can effectively eliminate the system mechanical structure noise and guarantee the stability of the nanometer positioning control system.
    Energy Efficiency Optimization of Power Plant Coal Conveyor System Based on Model Predictive Control
    REN Zhi-ling, ZHAO Xing, LIN Dong, ZHANG Guang-quan, ZHANG Zhong-bao
    2019, 26(7):  1372-1377. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the operation efficiency of belt conveyor for coal-fired power plant, an optimization approach is proposed. The mathematical model of the belt conveyor is built firstly, its optimal parameters are obtained by using the dynamic parameter analysis method based on the finite element model. Then the load shifting strategy is carried out with open loop optimal control. Finally, the model predictive control is used with feedback correction and rolling optimization because of the control error due to interference. The results show that the model predictive control strategy can save energy remarkably, reduce production cost greatly, increase production efficiency of power plant, and have good practical application value.
    Study of a Static and Dynamic Combined Loading System for Anomalously Low Friction Rockburst
    ZHANG Jian-zhuo, ZHANG Jia-Lin, WANG Jie, LI Li-ping
    2019, 26(8):  1550-1555. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to realize the vertical static-dynamic combined accurate loading of anomalously low friction rockburst test platform, an electro-hydraulic servo system based on force control is designed. Firstly, based on the mathematical model of the system, the influence of static loading on dynamic loading system is studied. Then, this paper uses AMESim software to study the influence of maximum no-load flow rate of servo valve and the open-loop gain on system performance. Finally, an anomalously low friction rockburst test platform is established to carry out static-dynamic combined loading test. The results show that the higher the maximum no-load flow rate is, the greater the system bandwidth is, and the greater the system energy loss is, and the open-loop gain of the system is reasonably selected according to the performance index. The electro-hydraulic servo static and dynamic combined loading system can realize static-dynamic combined loading with static load of 0~500 kN, dynamic load amplitude of 0~50 kN and frequency of 0~25 Hz.
    Research on Modeling and Path Planning of Urban Sanitary Vehicle Dispatching System#br#
    #br#
    CHEN Mei, LI Bing-hui, PAN Wang-yang
    2019, 26(9):  1751-1755. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the running route of urban sanitary vehicle and reduce the total cost, this paper builds a mathematical model of path planning for urban sanitation vehicle dispatching system with garbage, sorting center, recycling enterprises, incineration plant and landfill. The hybrid algorithm of genetic algorithm and tabu search algorithm was applied to the path planning of sanitation vehicle, and the total cost was minimized as the objective function. The algorithm was designed and simulated according to the actual case. The simulation result shows that the algorithm has good convergence and good feasibility and operability. The conclusion of this paper is of great significance to improve the operation route of urban sanitation vehicles and reduce the total cost.
    Voronoi Map Localization Algorithm Based on Geometric Modification of Multi Anchor Nodes
    XIA Lei, TAN Zhi
    2019, 26(10):  1939-1943. 
    Asbtract ( )  
    Related Articles | Metrics
    According to the error caused by imperfect direct distance ranging technology in static networks, an improved Voronoi graph localization algorithm based on geometric constraint is proposed. The Cayley-Menger determinant is introduced to limit the distance relation, and the constraint equation of distance error is obtained, and then the optimal problem is solved by using the Lagrange multiplier method, the distances between nodes satisfy the true geometric constraints after the optimization. At the same time, the distance information is applied to the location of many anchor nodes. At last, the modified distance is applied to the Voronoi map positioning algorithm to optimize the algorithm. Simulation results show that the proposed algorithm is superior to the traditional positioning algorithm based on Voronoi map, which can effectively improve the success rate of positioning and positioning accuracy, and it has wider application scope.
    The Intrusion Detection Model Based on Hesitant Trapezoid Fuzzy Algorithm
    JIANG Ming-fu
    2019, 26(11):  2109-2114. 
    Asbtract ( )  
    Related Articles | Metrics
     For the intrusion detection model selection problem under the hesitant trapezoidal fuzzy information, an approach based on the hesitant trapezoid fuzzy decision making algorithm is proposed to select the intrusion detection model. First, considering the decision information is hesitant trapezoidal fuzzy number and the attributes are interrelated, based on the hesitant trapezoid fuzzy operational laws, the hesitant trapezoid fuzzy weighted average (HTrFEWA) operator and the hesitant trapezoid fuzzy weighted geometric (HTrFEWG) operator are presented. Then, for the fact that the ordered position of the hesitant trapezoid fuzzy set has different weights, the hesitant trapezoid fuzzy ordered weighted average (HTrFEOWA) operator and the hesitant trapezoid fuzzy ordered weighted geometric (HTrFEOWG) operator are proposed, which is followed by the discussion of their desirable properties. Finally, a new method for multi-attribute decision making is investigated based on the HTrFEWA operator and HTrFEWG operator, and applies the example for the selection of intrusion detection model to demonstrate the method’s practicality and effectiveness.

    Research on the Cloud Computing Models Based on the Improved Interval Cross Efficiency

    WU Gui-ming
    2019, 26(12):  2246-2251. 
    Asbtract ( )  
    Related Articles | Metrics
    The traditional DEA (Data Envelopment Analysis) cross efficiency measures the efficiency by solving a model, which may can't consider the relation of competition and cooperation between DMUs (decision making units) and can’t rank to all DMUs fully. For interval DEA, three models are utilized to measure efficiency of decision making units. These three models, including aggressive, benevolent and competing cross-efficiency models, considering both competition and cooperation among DMUs. The classified model is improved in third model and put forward a method to classify the discrete data by interval neighborhood mutual information. Then, the latent information function is applied to get the weights of above mentioned three models for every decision making unit and aggregate efficiency scores of different models in accordance with the OWA operator. In addition, based on the aggregative efficiency scores, the decision making units are ranked. In the end, a numerical example about selection of cloud computing models is used to verify the rationalization and feasibility of the proposed method.
    The Decision-making Model to Select Network Systems Based on the Hesitant Fuzzy Geometric Algorithm
    GAO Ya-li
    2020, 27(1):  148-154. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at multi-criteria group decision making (MCGDM) problems where criteria values are hesitant fuzzy information and criterions are associated with each other, a generalized hesitant fuzzy geometric Bonferroni mean (GHFGBM) operator is proposed on the basis of Archimedean T-norm and S-norm, and then a novel computer network system selection model is designed. The advantages of the developed method are not only its capability to capture the interrelationship among the input variables, it also enables the model method to be applied to other fields. Some desirable properties of the GHFGBM operator are discussed, including Permutation invariance, monotonicity, boundedness and idempotence and so on. Some special cases are obtained if the parameter and additive operator takes different values and functions. In the end, a numerical example about update alternative of computer network system selection to illustrate the rationality and effectiveness of the proposed model.
    Research on the Detection Algorithm of the Vehicle and Vehicle Distance Based on the Single and Double Camera Switch
    DU Yan-qi, CHEN Meng-yuan
    2019, 26(2):  327-335. 
    Asbtract ( )  
    Related Articles | Metrics
    The range of interest (ROI) of the vehicle detection is defined after the lane has been detected, then according to the characteristics of the vehicle vertical direction, shadow under vehicles and taillight features to lock the front vehicle position, and the feature information of vehicles are converted into vehicle distance information finally. The algorithm proposed in this paper treats differently with day and night, and utilizes the strategy of single and double camera handover to detect the vehicle distance, which makes the system in short distance vehicle distance detecting with excellent performance. Experiments show that, this system designed in the paper, achieves the anticipated function, can accurately detect multi-lane and short distance vehicle distance, and the efficiency of the system also meets the real-time requirement.
    Scheduling Two-agent Parallel Machine with Release Times
    ZHANG Jia, QIAN Bin, HU Rong, WU Li-ping
    2020, 27(02):  368-373. 
    Asbtract ( )  
    Related Articles | Metrics
    This paper considers two-agent scheduling with release times where agent A and agent B have to share m parallel machines for processing their jobs. The objective of agent A is to minimize the total completion time, while the objective of agent B is to ensure its total completion time under a fixed value. Firstly, the considered problem is proved to be NP-hard under the single machine condition. Secondly, a pseudo-polynomial-time algorithm is proposed by using the dynamic programming (DP) method, and then a fully polynomial-time approximation algorithm is further provided.
    Parameter Optimization of Belief-rule-base Based on an Improved Differential Evolution Algorithm
    ZHANG Qin-li, HU Rong, ZHOU Zhi-jie, QIAN Bin
    2019, 26(3):  555-559. 
    Asbtract ( )  
    Related Articles | Metrics
     In view of the current study on the belief rule base (BRB), the prerequisite attribute, belief degree and the size of the structure of the rule base are given by experts, which will make BRB be limited in expert knowledge and could lead to the parameters of BRB inaccurate. This paper puts forward an improved differential evolution algorithm (IDE) to optimize parameters of BRB. In IDE, the mutation strategy is randomly selected to maintain the diversity of population, and a simple local search is used to balance the global and local search ability of DE. Finally, experiments are carried out with tipping paper permeability test data taken by a Chinese cigarette factory. The experimental results show that the optimization of BRB of the proposed method is simple and effective.
    A Belief Rule Based Inference Method for Process Alarm Prognosis
    ZHANG Ze-sheng, LI Hong-guang, YANG Bo, ZHANG Jing
    2019, 26(4):  765-772. 
    Asbtract ( )  
    Related Articles | Metrics
    To better utilize historical alarm information of industrial processes, this paper introduces a belief rule base model based process alarm time series prognosing inference approach which is able to evaluate the process safety performance in the future. The belief rule base model involved is established using historical alarm data of process variables, while a particle swarm optimization algorithm is used for the model parameter learning. The online implementation of the model can help predict trends of the process alarm states in the future. A numerical simulation and industrial process alarm data are used to demonstrate the effectiveness of the approach with satisfying prognosis results.
    Power Monitoring System Based on Compressive Sensing
    LI Rong, ZHOU Si-wang
    2019, 26(5):  952-956. 
    Asbtract ( )  
    Related Articles | Metrics
    Using WSN to monitor the grid can save a lot of manpower costs and improve data collection in real time. However, the real-time sampling produces large amounts of data and will put pressure on the communication link and also increase energy consumption. Therefore, a compression sensing model is proposed. An improved two-step iterative threshold algorithm is used to compress the power data. By reducing the data sampling rate, the pressure on data links and communication systems is reduced and the delay is effectively reduced. And the data reconstruction is performed on this basis. The experimental results show that, compared with the computational complexity of back propagation (BP) and the low convergence rate of iterative soft thresholding (IST), the model can effectively reduce the data sampling rate and power consumption.
    Interconnected Power System Load Frequency Control Based on Super-capacitor
    Super-capacitor, interconnected power system, load frequency control, fuzzy control
    2019, 26(6):  1158-1162. 
    Asbtract ( )  
    Related Articles | Metrics
    A fuzzy-logic controlled super-capacitor to improve the load frequency control (LFC) of an interconnected power system is proposed in this paper. The load perturbation unbalances the generation output power and load demand power, the primary target of interconnected power system load frequency control is to maintain the frequency and tie-line exchange power in normal range. In the proposed method, the frequency deviation is used as the input of the fuzzy-logic controller, the super-capacitor in each area is interfaced with a bidirectional Buck-Boost converter, which is used to control super-capacitor to charge or discharge. When the load suddenly changes, the super-capacitor will release or absorb power from the system to ensure the power system stable. The simulation results show that the fuzzy-logic controller can suppress frequency deviation caused by load power fluctuation, thus the load frequency control targets can be satisfied, and this method also has good robust and dynamic characteristic.
    Anti-swing Control of Bridge Crane Based on Model Predictive Algorithm
    HU Fu-yuan, SHAO Xue-juan, ZHANG Jing-gang
    2019, 26(7):  1378-1383. 
    Asbtract ( )  
    Related Articles | Metrics
    The main control objective of bridge crane systems is to transport cargos to the desired location rapidly and accurately, with cargos swing being as small as possible in the transportation process. In order to tackle this problem, a differential flatness theory based model predictive control approach is presented in this paper to guarantee playload to reach desired location rapidly and accurately while simultaneously limiting swing of playload within a safe range. According to the differential flatness property of bridge crane systems, a predictive model in form of differential flat outputs with a simple structure is established, and dynamic characteristics of the model are used to achieve system optimum online. Simulation results illustrate the proposed method can achieve bridge crane’s trolley positioning rapidly while simultaneously limiting playload's swing angle within a permitted range.
    Kalman Filter Complementary Fusion Method Based on Hammerstein System
    WANG Jiang-hua, ZHANG Li, SUN Si-fan
    2019, 26(8):  1479-1483. 
    Asbtract ( )  
    Related Articles | Metrics
    As a non-linear, multi-variable and highly coupled underactuated system, the quadrotor UAV's underactuated characteristic can cause instability of the quadrotor nonlinear link, and then cause interference to the strapdown inertial measurement system. To solve this problem, first analyze the structure and characteristics of the quadrotor underdrive system, and on the basis of which establish the Hammerstein nonlinear model of the quadrotor UAV system by reference to the composition of the traditional Hammerstein nonlinear system. Then we design a new Kalman-type scroll window complementary fusion filtering algorithm and verify the performance of the algorithm on the underactuated Hammerstein system of quadrotor drone. Simulation and physical test results show that the fusion filtering algorithm has good smoothness and fast followability. It can minimize the interference of external noise on the quadrotor flight control under the premise of ensuring the system response speed, and effectively solve the validity and stability issue of the data collected by the strapdown inertial measurement system under complex conditions.
    Voltage Stability Analysis of Distribution Network Considering Variable Correlation#br#
    #br#
    TAI De-qun, ZHOU Song-lin, ZHANG Bi-xi, SUN Chang-xiang, LUO Xi
    2019, 26(9):  1756-1762. 
    Asbtract ( )  
    Related Articles | Metrics
    The distributed photovoltaic generation system connected to distribution network has strong randomness and weak controllability, which combined with random loads will cause the uncertainty of the power flow in distribution network. For simulating the correlation between photovoltaic generation and photosensitive load in the calculation of probabilistic power flow, the joint probability distribution model about the two random variables is established on base of Copula function. The time-ordered samples with certain correlation are obtained by Latin hypercube sampling technology firstly, and then are substituted into equations of power flow to calculate joint probability distribution of power flow. The simulation results of IEEE33 distribution system show that the probabilistic power flow considering the correlations of random variables are more in line with the actual, and are more helpful to analyze the probabilistic stability of node voltage.

    Direct Torque Control of Brushless DC Motor Based on the Second-order Sliding Mode Observer

    ZHAO Hong-fei, ZHAO Zhi-cheng, ZHANG Jing-gang
    2019, 26(10):  1944-1949. 
    Asbtract ( )  
    Related Articles | Metrics

    To solve the difficulty of acquiring back electromotive force (back-EMF) and the chattering problem existing in the conventional sliding mode control, a direct torque control (DTC) based on the second-order sliding mode observer (SOSMO) is proposed for brushless DC motor (BLDCM). According to the mathematical model of BLDCM, traditional linear sliding mode surface and its first-order derivative are selected to constitute the second-order sliding mode surface. Simultaneously, the control law was deduced by using an improved reaching law. Then, the SOSMO was designed, and it could make the sliding mode chattering be focused on the higher order differential of phase error and integrate the higher order differential term. So, the weaker chattering and faster convergence was guaranteed. Moreover, the back-EMF could be accurately estimated by SOSMO without an additional low-pass filter. The SOSMO was applied to DTC of sensorless BLDCM, and the torque ripple and system performance could be improved effectively. The simulation results show that the proposed method is superior.

    A Design Method for Deep Belief Network Based on Reinforcement Learning

    XING Hai-xia, CHENG Le
    2019, 26(11):  2115-2120. 
    Asbtract ( )  
    Related Articles | Metrics
    In recent years, deep learning-based deep belief network (DBN) has achieved successful applications in artificial intelligence and big data prediction analysis. However, too many hidden layers in DBN easily leads to a poor learning accuracy of supervised fine-tuning method (BP algorithm), even failure because of gradient diffusion, and robustness is poor. For this problem, an improved DBN based on reinforcement learning (RL-DBN) is proposed. First, adaptive contrastive divergence (ACD) algorithm is used to fast pre-train the hidden layers of DBN so that the better initial weight can be achieved, then the RL algorithm is used to replace BP algorithm to fine-tune DBN so that higher accuracy and better robustness can be achieved. The experimental results show that, compared with several existing similar models, the proposed RL-DBN achieves better performance in learning rate, accuracy and robustness. 

    Research on Fast Defogging Algorithm Based on Depth Evaluation of B Channel Compensation

    YUAN Gui-xia, ZHOU Xian-chun
    2019, 26(12):  2252-2257. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the effect of image defogging and take into account the initial details and brightness, a fast defogging algorithm based on B-channel compensation for depth of field estimation is proposed. Firstly, the atmospheric scattering model is analyzed. According to the relationship between B-channel and fog concentration, the depth of field estimation model of B-channel is constructed, and the absolute difference of R and G-channel components is used to compensate the depth of field of B-channel. In order to prevent the over-compensation of near-field and the missed compensation of long-range, the B-channel component of image is used to construct the segmentation compensation model to compensate the gray value of far-range and near-range pixels. The depth-of-field assessment map is formed by setting half-attenuation factor and modifying depth-of-field map. Finally, minimum filter and guide filter are used to optimize depth-of-field map to achieve image defogging effect. The experimental results show that, compared with the current image defogging technology, the proposed algorithm has better defogging effect and better preservation of image details and brightness.
    Multi-stages Dispatch Strategy Optimization for Flight Based on Discrete and Dynamic Programming
    CHEN Hua-qun
    2020, 27(1):  155-161. 
    Asbtract ( )  
    Related Articles | Metrics
    Flight dispatch is the core of operational control. To realize global plan and quantitative assessment of operational dispatch release and control strategy, an multi-strategy framework is put forward based on minimum cost with shortest path. Qualitative technical means was changed just relying on traditional manual interpretation experience. Two-dimensional shortest path was constructed for flight state transition influenced by assignment strategy. Discrete dynamic programming mathematical model was made based on shortest path . Reverse recursive equation of minimum cost was established. Numerical calculation method was used to obtain the optimal dispatch strategy in tabular form. Quantitative evaluation and combinatorial optimization of non-linear and discrete composite dynamic programming problems such as flight operation decision-making were solved. Finally, feasibility and superiority of algorithm was test by simulation experiment. The experimental results show that, compared with time sequence operation mode of separate stage, the proposed algorithm is much better in global optimization for airlines operational control in whole course.
    Functional Safety Analysis of Level Transition Process of CTCS-3 System
    2019, 26(2):  336-342. 
    Asbtract ( )  
    Related Articles | Metrics
    Aimed at the complex compositeness of level transition scenes of the CTCS-3 system, according to the CTCS-3 system functional requirements specification, selecting the demand of the system life cycle stage, the safety of level transition scene is studied. Firstly, based on the UML extensibility mechanism, the hybrid UML model is established, complex compositeness of level transition scene is described. Secondly, according to the CTCS-3 system functional requirements specification, functional requirements are summarised, the correctness of level transition scenes is verified. Then, by analyzing the level transition process, the possible faults of function modules of system components are found out. The fault model of level transition scenes is established using FFDN. By integrating the PHAVer model and the fault model, the PHAVer model containing faults is built. Finally, functional module failures when functional requirements of level transition scenes are not satisfied are analysed with PHAVer, the function safety analysis of level transition scenes is implemented.
    Adaptive Estimation of Distribution Algorithm for Solving a kind of Distributed No-waiting Flow Shops
    ZHANG Zhen-lei, BAI Liang, HU Rong, QIAN Bin, CHE Guo-lin
    2020, 27(02):  374-379. 
    Asbtract ( )  
    Related Articles | Metrics
    With the development of the economy, distributed permutation production becomes more and more widespread in all walks of life, more attention is put on distributed models. An adaptive estimation of distribution algorithm(AEDA) is proposed for solving no-wait distributed permutation flow shop with Sequence Dependent Setup Times and Arrival times(NDPFSP with SDSTs and RDs) and minimizing the largest completion time. First of all, this paper proposes the earliest completion factory with arrival time(ECFAT), which is more suitable for this problem, canmake a judgment in the generation process of solution and improve the quality of the current solution faster. Next, according to different problem scales, the proposed local search can adjust the depth of local search to ensure its ability for solving this problem.
    A Rat SLAM Model Base on Improved Closed-loop Detection Algorithm
    XU Tong, WU Xue-juan, LING You-zhu, CHEN Meng-yuan
    2019, 26(3):  560-565. 
    Asbtract ( )  
    Related Articles | Metrics
    The performance of the Rat SLAM model gets worse under the condition of the changing light, a closed-loop detection algorithm based on real-time key frame matching is proposed, this algorithm better estimates the closed loop assumption in the future by storing different signatures under the same location, which improves the matching rate of complex scenes under the circumstance of the angle of light changes. In the meantime, the improved closed-loop detection algorithm improves the real-time performance of the traditional closed-loop detection algorithm by referring to the mechanism of human brain memory. This algorithm is fused into the Rat SLAM model and experiments are done respectively from the visual template of local view cells, the matching effect of the experience nodes, and the experience map by the qualitative approach. Experiments show that compared with the traditional closed-loop detection, the improved closed-loop detection algorithm has stronger robustness under the circumstance of the angle of light changes and has better real-time performance.
    Research on Multi-class Mixed Face Recognition Based with RBF Support Vector Machine
    ZHU Shu-xian, LI Yun, ZHU Yong-jun, WU Zheng-tian
    2019, 26(4):  773-776. 
    Asbtract ( )  
    Related Articles | Metrics
    RBF support vector machine (SVM) is widely used in pattern recognition and fault detection because of its stability and high recognition rate. Unlike other literatures, this paper applies RBF support vector machine to multi-class mixing face recognition. On the one hand, after multi-class mixing, the performance of RBF kernel function for support vector machine is examined whether investigated or not. On the other hand, this method has more practical value. Experiments show that the performance of multi-class mixing samples is slightly degraded compared with that of single-class RBF support vector machine, but the recognition rate is still very high, which verifies the effectiveness and practicability of the method.

    Sparse Auto Encoder Model Based on Firefly Learning Optimization and its Application in Bearing Fault Recognition

    DU Can-yi, LIN Zu-sheng, ZHANG Shao-hui
    2019, 26(5):  957-964. 
    Asbtract ( )  
    Related Articles | Metrics
     Sparse Auto Encoder (SAE) finds a set of "super-complete" base vectors to mine the intrinsic structure and pattern of input data, which enables high-level output to better express the category information of input samples. Its good performance of dimension reduction has been widely concerned and gradually applied in fault diagnosis of mechanical equipment. However, the feature number of hidden layer in SAE model directly affects the expression effect of high-level output on low-level input mode. Simply setting the feature number of hidden layer is difficult to achieve ideal recognition effect. Aiming at this problem, the optimal feature number of each hidden layer is determined by using the advantages of the firefly learning algorithm, and the optimal SAE model is determined. Bearing simulation and fault state recognition experiments show that sparse automatic coding model can achieve better recognition effect than shallow structure and random parameter SAE model under different test samples after the number of hidden layer features is determined, and the recognition accuracy is higher.
    Research on Economic Optimal Operation for Micro-grid Based on Demand Response
    LUO Xin, ZHAO Feng, LI Ying
    2019, 26(6):  1163-1169. 
    Asbtract ( )  
    Related Articles | Metrics
    Economic optimal operation of micro-grid is a significant direction of micro-grid research. In order to realize the comprehensive optimization of distributed generation-grid-loads of micro-grid, the resources including power supply side and demand side are fully considered with combination of the transferable load model under demand response and the economic optimal operation model of micro-grid in this paper, the chaotic firework algorithm (C-FWA) is used to optimize the load of demand side and the active power output of the power supply side synthetically, and the validity and feasibility of C-FWA for solving this type of problem are verified. The simulation results show that the economy of the micro-grid system is improved when the resources of power supply side and the demand side are fully taken into account, and the roles of peak clipping and valley filling are played in grid-connected operation mode. 
    Modeling and Sliding-mode Control for the Automotive Electronic Throttle
    BAI Rui, WANG Sheng-xian, WANG He-bin
    2019, 26(7):  1384-1390. 
    Asbtract ( )  
    Related Articles | Metrics
    The main function of electronic throttle is to regulate the air inflow into the engine system of the vehicle by changing the opening angle of the valve plate. The nonlinear mathematic model of the electronic throttle is proposed based on the mechanism and work principle. In the proposed model, the nonlinear factors spring and friction and the external disturbance caused by the gas flowrate are considered. Therefore, the proposed model can describe the nonlinear characteristics of the electronic throttle. Based on the proposed model, the sliding-mode control is designed for the electronic throttle, which can handle the strong nonlinearity and external disturbance of the electronic throttle. The closed-loop stability is proved. The control experiment platform of the electronic throttle is developed. Computer simulation and experiments are implemented. The research results of the simulation and experiment show that the proposed controller can make the actual angle of the electronic throttle track its set point with the satisfactory performance, and the external disturbance can be effectively suppressed.
    An SLAM Method for Chaos Optimization Based on Chicken Swarm Algorithm
    GE Yuan-yuan, ZHANG Hong-ji
    2019, 26(8):  1509-1514. 
    Asbtract ( )  
    Related Articles | Metrics
    For robot in unknown environment, using particle swarm optimization algorithm to simultaneous localization and mapping (SLAM), error location accuracy is not high, direction error as well as the problems of poor robustness, puts forward an improved SLAM method based on chaos theory in chicken swarm algorithm. First, introduced the study mechanism of chicken swarm algorithm, through learning coefficient of chicken swarm algorithm in chaotic mutation, then using chaotic search to disturbance the chicken swarm of each subgroup, at the same time in the optimal location of the adaptive chaotic search to find the population within the territory of the optimal location. The algorithm is simulated and compared with the SLAM algorithm based on particle swarm optimization. The simulation results show that the proposed algorithm can obtain higher positioning accuracy and precision of map building and better estimation stability.
    Hidden Markov Model Based Non Parametric Bayesian Algorithm For Video Anomaly Detection
    CHEN Hao-gui, XU Le-ling, TANG Xu-qing
    2019, 26(9):  1763-1769. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the applicability of video anomaly detection algorithm, and improve the recognition accuracy and efficiency of the algorithm, we proposed an hidden markov model based non parametric bayesian algorithm for video anomaly detection. Firstly, the video sequence is divided into several segments, and then the total number of optical flow vectors and the feature vectors are extracted for all the pixels of all frames; Then, in order to solve the problem of mode number unknown in current data segmentation and hidden patterns, we used the Hidden Markov algorithm of the hierarchical Dirichlet process and nonparametric bias factor analysis to make video data stream segmentation and pattern discovery; Finally, an interactive system was introduced to allow users to check and view suspicious events. The experimental results show that the proposed algorithm can realize the adaptive pattern discovery of video anomalies and improve the recognition accuracy and efficiency of the algorithm.
    Study on Dynamic Optimal Control of Fed-batch Fermentation Process
    LI Hai-bo, PAN Feng
    2019, 26(10):  1950-1954. 
    Asbtract ( )  
    Related Articles | Metrics
    In the biochemical process, such as ethanol fermentation, some problems such as high nonlinearity and poor stability cause more difficulties on the optimal control of the fed-batch process. In order to solve these problems and improve the optimization efficiency as well as maximizing the product concentration, rolling optimization strategy is proposed based on the core idea of predictive control. In the optimization process, the penalty function method was used to transform the original optimization problem with constraints into an unconstrained optimization problem. And hybrid optimization algorithm combining ant colony algorithm and iterative dynamic programming has been applied into the substrate flow rate control trajectory optimization. Compare this new optimization algorithm with ant colony algorithm, the simulation results show that some performances such as optimization speed, optimization performance have been improved greatly.

    Research on Dynamic Access Selection of RSU in VANET

    ZHANG Ying, LI Pei-song, XIONG Wei
    2019, 26(11):  2121-2129. 
    Asbtract ( )  
    Related Articles | Metrics
     Real-time communication problems of vehicle to vehicle and vehicle to infrastructure in VANET (Vehicular Ad hoc Network, VANET) have been taken more and more attention by researchers. The high speed mobility of vehicles and the unreliability of wireless communication greatly reduced the efficiency of data transmission. In order to solve this problem, the attention is focused on the dynamic access selection of RSU (Road Side Unit, RSU) in VANET and a new RSU selection algorithm is proposed to allocate vehicles access to related RSUs. The conventional access method is based on the signal strength of vehicles received from related RSU, but it does not take full account of the high speed mobility of vehicles which will lead to a vast variability of number of vehicles connected to RSU. In this paper, a method of real-time monitoring and forecasting is used to adjust certain vehicle connect on reasonable RSU to make the load of each RSU as much as balance, which will minimize the variability of the number of vehicles connected to each RSU, and ensure the RSU can be fully utilized. Simulation results show that the proposed algorithm can reduce the message collision, enhance the probability of collision free transmission, and improve the successful packet transmission rate effectively.

    Prediction of Room Cooling Load Based on Improved ARX Model

    TAI Min, LI Zhan-pei, LIU Ting-zhang, JIN Bi-yao, XUE Fan
    2019, 26(12):  2258-2263. 
    Asbtract ( )  
    Related Articles | Metrics
     Accurate prediction of real-time cooling load is the fundamental work for optimizing the operation of air conditioning systems. Inspired by interval partitioning of variables, two improvements of ARX model are proposed, which are based on temperature index and least squares support vector machine (LSSVM), to solve the problem that traditional ARX model based on outdoor weather parameters and historical cooling load has low universality. Compared with the traditional ARX model, simulation results show that accuracies of the two proposed models are both greatly improved. The ARX model based on LSSVM has the highest prediction accuracy and universality.
    Research on Nash Equilibrium Based on Improved Quantum Particle Swarm Algorithm#br#
    #br#
    ZHANG Lei
    2020, 27(1):  162-167. 
    Asbtract ( )  
    Related Articles | Metrics
    In the process of solving the Nash equilibrium problems related to N-person non-cooperative game, quantum uncertainty principle, co-evolution and antibody concentration suppression mechanism in immune algorithm were introduced into the classical particle swarm optimization, and a new improved quantum particle swarm optimization algorithm is designed to deal with Nash equilibrium problems. In the process of calculation, this algorithm utilizes antibody concentration and co-evolution to maintain the diversity characteristics of particle groups, and uses the uncertainty of quantum to decrease the time-consuming of iterative searching process. In addition, this algorithm not only effectively inherits the simplicity and convenience of particle swarm optimization, but also greatly improves the convergence speed and global search ability. The experimental results show that the improved algorithm can overcome the premature convergence of particles, and has better performance than genetic algorithm and immune particle swarm optimization.
    Research on Power Grid Fault Forecast Based on Abductive Reasoning Network
    LIU Xiao-qin, WANG Da-zhi
    2019, 26(2):  343-348. 
    Asbtract ( )  
    Related Articles | Metrics
    Fault diagnosis is usually judged according to the information after fault happens. In order to prevent the fault before the occurrence of the fault, model prediction (MP) and abductive reasoning network (ARN) are proposed to predict the power grid fault. MP predicts the trouble-free operation of the data of the power grid using the historical data, compares with the actual grid runtime data and calculates the difference. ARN handles complicated relationships between data processing and the corresponding candidate fault section using a hierarchical network with several layers of function nodes of simple low-order polynomials. The combination of model prediction and abductive reasoning network can locate the fault before the protection device and circuit breaker acts, and has the function of fault early warning. The simulation results show that the diagnosis system can obtain rapid and accurate diagnosis results compared with the neural network method.
    Air-conditioning Cooling and Heating Load Prediction Based on Periodic ARMA-SVR Model
    GAN Zhong-xue, YU Xiang-xiang, XU Yu-li, LI De-wei
    2020, 27(02):  380-385. 
    Asbtract ( )  
    Related Articles | Metrics
    For industrial users, the prediction of air-conditioning load can be great helpful to reduce the energy consumption. Besides the nonlinear character, the user's load data is also very sensitive to the external disturbance and with daily periodic characteristics. This makes the traditional ARMA and SVR methods hard to achieve good prediction. Therefore, a method of combining ARMA model and SVR model with daily periodic characteristics is presented. Firstly, combined with the daily periodic characteristic of the raw data, the ARMA model is used for linear prediction. For the nonlinear characteristics of original data which retained in the prediction residuals of ARMA model, the SVR model is used to predict the nonlinear part of the residuals and modify the prediction result, obtaining the final predicted value. Experimental results using actual data show that the proposed method can significantly improve the prediction performance.
    Hysteresis Modeling of Extreme Learning Machine Based on Duhem Operator
    PAN Hai-peng, JIANG Hui-bin, ZHAO Xin-long
    2019, 26(3):  566-569. 
    Asbtract ( )  
    Related Articles | Metrics
    Piezoelectric actuators (PEAs) have been widely used in the field of high-precision positioning, but there is inherent hysteresis nonlinearity which seriously degrades the tracking performance. In order to improve the control precision of the high-precision positioning system, the nonlinear hysteresis model is established. In this paper, an identification method using extreme learning machine based on Duhem operator is proposed. The Duhem operator is proposed to describe the relationship between the system input and the system output, and the hysteresis model is achieved by using extreme learning machine and Duhem operator. Finally, simulation results are given to evaluate the effectiveness of the proposed modeling method. The method has improved the identification speed and precision significantly.
    Research on Position Sensorless Control of PMSM Based on Cubature Kalman Filter
    WANG Di
    2019, 26(4):  777-782. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to overcome the problems of model inaccuracy and external disturbance led to the decrease of the kalman filtering accuracy, an improved cubature kalman filter is set up in permanent magnet motor position sensor less control algorithm. The state equation of Permanent magnet motor in the two-phase stationary coordinates is established, and gaussian process regression is used to identy the system state and measurement, and alternative cubature kalman filter in the system state equation and measurement equation. The identification accuracy of cubature KF is retained, the system robustness is improved with model inaccuracy and external disturbance. The experimental results show that the improved cubature kalman filtering algorithm identification accuracy, real-time, and robustness are better than kalman filter and extended kalman filtering and cubature kalman filtering algorithm, and it has a wider application prospect.

    Key Frame Abstraction and Retrieval of Videos Based on Deep Learning

    LIANG Jian-sheng, WEN He-ping
    2019, 26(5):  965-970. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the efficiency and accuracy of video retrieval, a schema of key frame abstraction and retrieval of videos based on deep learning is proposed. Firstly, an adaptive key frame selection algorithm is designed, and the distances of wavelet transforms are used to detect the frames belong to the same shot; then, abstract information of each shot is abstracted, and the frames containing the most significant features are set as the key frame of the corresponding shot; lastly, the existing convolutional neural network framework is used to abstract the features of key frames, and unsupervised, semi supervised and supervised retraining models are designed to improve the effect of the feature abstraction of the convolutional neural network and the accuracy of the video retrieval. Experimental results based on the public video datasets show that the proposed schema realizes a good precision for video representation, and it realizes an accuracy and high efficiency video retrieval too.
    BP Model of Coke Quality Optimization by Adaptive Differential Algorithm
    DU Ji-dong, TAO Wen-hua, LI Shao-peng, GU Qi-yao
    2019, 26(6):  1170-1176. 
    Asbtract ( )  
    Related Articles | Metrics
     In order to solve the problem that the ash Ad, the sulfur fraction Std, the crushing strength M40 and the wear strength M10 in the coke quality index are difficult to measure in real time, an adaptive differential evolution algorithm (ADE) is proposed to optimize the BP network (ADE-BP) coke quality prediction model. Based on the actual input and output index system, the model is trained and simulated according to the historical data of the actual coking production process. The simulation results show that the adaptive differential evolution algorithm to optimize the coke quality model of BP network has higher prediction accuracy. This study provides a new idea for the difficult problem of coke quality index in coking production process, which can provide theoretical basis for high efficiency and low consumption production in coking industry.
    Synchronization Method between Control and Communication in the System based on EPA Real-time Ethernet
    LIU Ning, LV Kun, XUE Tong-long
    2019, 26(7):  1391-1396. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the real-time performance of EPA (Ethernet for Plant Automation) system, EPA-CCS (EPA Control and Communication Synchronization) method that accomplishes the synchronization between control and communication in EPA system is proposed. On the base of EPA deterministic scheduling mechanism, EPA-CCS method divides EPA macro cycle into two parts: communication time slice and control time slice. EPA device acquires the current time during its each round scan and determines whether to implement its communication task or to implement its control task according to whether the current time is in the communication time slice or in the control time slice. When the control task is implemented, EPA device ensures the function blocks can be implemented only once in a macro cycle through setting and scanning state signs. An experiment proves that this method can effectively avoid the invalid executions of function blocks and the invalid transmission of data, so that the operation efficiency and the real-time performance of EPA system are improved.
    Improved Particle Swarm Optimization Algorithm and its Application Path Planning
    WANG Chuang, DONG Hong-li, GU Xing-shu, LI Jiahui, CHEN Jian-ling
    2019, 26(8):  1466-1471. 
    Asbtract ( )  
    Related Articles | Metrics
    This paper is concerned with a novel Random Delayed Particle Swarm Optimization (RDPSO) algorithm which is proposed for the disadvantages of standard particle swarm optimization algorithm, such as fast convergence speed in the early stage, premature in the later period and local trapping phenomenon in the searching process. In this algorithm, the velocity update model switches from one mode to another according to the expectation of the random variable. Furthermore, in order to reduce the occurrence of local trapping phenomenon and expand the search space in the searching process, the random time-delays are introduced to the velocity updating equation. A simulation example is provided to verify that the integrated performance of the proposed algorithm is better than the other improved PSO algorithms. Finally, the RDPSO algorithm is applied to the UAV path planning in oilfield inspection. Experiments show that the RDPSO algorithm can simultaneously avoid the occurrence of local trapping phenomenon and ensure the convergence speed.
    Research on Optimization of Parallel Computing for SOM Image Segmentation on GPU
    YANG Fei, LI Jing, ZHOU Liang
    2019, 26(9):  1770-1775. 
    Asbtract ( )  
    Related Articles | Metrics
    To accelerate the segmentation method of self organizing map (SOM), the original serial method is extended to the parallel method, and the corresponding parallel computing module is designed for the specific image segmentation method. In order to reduce the computational load, by minimizing the non block edge pattern vector in-class covariance matrix to the ratio between class covariance matrix, the ratio function is calculated. And the number of segmentation is estimated by the ratio between in-class scatter matrix and class scatter matrix. Segmentation of brain magnetic resonance imaging (MRI) images shows that the proposed parallel optimization method has greatly improved the computational efficiency under the premise of ensuring the quality of image segmentation in comparison with the original serial method. And its computing efficiency is higher than that of similar parallel acceleration method.
    The Multi-model Soft Sensor Modeling Based on Affinity Propagation Clustering
    XU Hai-xia
    2019, 26(10):  1955-1959. 
    Asbtract ( )  
    Related Articles | Metrics
    The data of a fermentation process is large, a single data-based soft sensor model suffers from heavy burden calculation and poor precision. In order to solve these problems, an improved multi-model soft sensor modeling method is proposed based on neural network and affinity propagation (AP) clustering. AP clustering algorithm is presented to solve the existed problems in original clustering algorithms, such as clustering number should be determined in advance and cluster accuracy depends on data distribution. Sub neural network models can be constructed based on the clusters. The proposed modeling method was applied to monitor the biomass concentration of an erythromycin fermentation process. Case studies show that the approach has better performance on calculation and accuracy.

    Node Deployment Algorithm Based on Linear Programming in UWSNs

    XU Yi-han
    2019, 26(11):  2130-2135. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at the detection of solid pollutants in waters, a mixed integer linear program-based 3D underwater wireless sensor networks deployment (MILP-UWSNs) algorithm is proposed to minimize the number of deployed underwater sensors with a target field installation while the coverage ratio must be satisfied. First, divide the deployment area into multiple sub cubes(Sub-Cubes), then use the mixed integer linear programming to calculate the minimum size of Sub-Cubes and ensure that the convergence time for deploying all Sub-Cubes is within an acceptable range. Finally, the effectiveness of the MILP-UWSNs algorithm is analyzed, and the MILP-UWSNs algorithm is compared with common similar algorithms. Experimental data shows that the proposed MILP-UWSNs algorithm is scalable and has good performance in terms of deployment cost and monitoring quality.

    An EDCA Flow Balance Scheme Using Probabilistic Access in WMN

    ZHU Ya-dong
    2019, 26(12):  2264-2269. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at the problem of unbalanced flow allocation among end-to-end in multi-interface oriented WMN, this paper proposed a local distributed EDCA flow balance solution based on probabilistic access. Uses of directional communication in a multi-interface mesh network introduced the problem of unbalanced flow allocation among the end-to-end flow that resulted in inefficient channel access using the standard EDCA mechanism. This paper modeled the problem of flow balance among end-to-end flow in multi-interface directional WMN as a convex optimization problem model. According to the convex property of aggregation problem, a local distributed solution was designed to solve the problem of flow balance allocation. Furthermore, an efficient probabilistic channel access mechanism was used in EDCA in order to guarantee the access requirements of a single interface in a mesh STA and achieve channel assignment. The simulation results show that the solution can balance network throughput and network capacity well and improve network performance.
    YU Qi, ZHANG Ying-ping, WU Jiao, FENG Xiao-wen, SUN Yue-jin, SUN Wen-yong, JIANG Ya-tong
    2020, 27(1):  168-173. 
    Asbtract ( )  
    Related Articles | Metrics
    With the advent of the big data era, as well as information security issues highlighted, enterprises' "Remove IOE" voice continues to rise. Considering the actual situation, different countries and different industries have different ways of dealing with "Remove IOE". Since the concept of "Remove IOE” was officially put forward by Alibaba., after the successful practice, the research and application of "Remove IOE " has been increasing. The domestic enterprises represented by Lenovo, Ali and Huawei have an increasing competitiveness in the fields of server, database and storage, providing mature products and services for "Remove IOE ". This paper introduces the process of "Remove IOE "in different fields, analyzes the difficulties and applications of "Remove IOE ", and summarizes the main solutions. Finally, combining the trend of big data era, this paper looks forward to the future of "Remove IOE ".
    Design and Analysis of Infants Sleep-monitoring System
    SHEN Xiao-bin, GU Tian-hua, CAI Bin-Bin, YE Hong-ji, ZHAO Jin-hui
    2019, 26(2):  349-355. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to realize the monitoring and recognizing of the infant’s sleep quality, a sleep monitoring system based on a simple chip microcomputer is proposed, which correspondingly includes a hardware design and a software system. The hardware system is mainly constructed by a MK60FX512VLQ15 system board, pressure sensors and a LCD display. The key working process of the software system is to use the data collected from the pressure sensors placed on the crib, and then calculate the parameters values of location, fluctuation range and change frequency of location by the proposed gravity center algorithm. The identification algorithm distinguishes the infant’s posture change and sleep patterns by calculating these three kinds of parameters. Finally, the rating of infants’ sleep status is outputted. Compared with some wearable types of bracelet sleep monitoring facilities, the proposed system achieves the intellectualization, visualization and extendibility of information.
    Research on Power Allocation in Cooperative Cognitive Radio
    SUN Ying-ying, ZHAO Hang, CAO Jun
    2020, 27(02):  386-390. 
    Asbtract ( )  
    Related Articles | Metrics
    针对协作无线电网络(Cooperative Cognitive Radio, CCR)的多中继分配和功率分配问题，提出了基于交叉熵的多目标优化(Cross-entropy-based Multi-objective Optimization, CEMOO)算法。该算法解决CCR网络中继分配和功率分配问题，即优化2个相互矛盾的目标：第一个目标就是最大化数据传输率；第二目标就是最小化温室气体排放。这2个目标的优化属非凸组合优化、NP问题。为此，使用基于蒙特卡洛的交叉熵优化(Cross-entropy Optimization，CEO)算法解决此非凸问题，避免产生局部最小或最大问题，进而获取复杂组合优化问题的解。仿真数据验证了CEMOO算法在多中继分配和功率分配方面的性能。
    Study on Control and Optimization of Indoor Environmental Quality Based on Model Prediction
    ZHAO An-jun, ZHOU Meng, YU Jun-qi, SUN Guang
    2019, 26(3):  570-577. 
    Asbtract ( )  
    Related Articles | Metrics
    In modern architecture, it is necessary to control and optimize the quality of indoor environment to ensure the high comfort and low energy consumption. Indoor environmental quality that contains a lot of uncertainties and nonlinear factors is difficult to be described by the traditional linear system. This paper takes the intelligent building laboratory of Xi'an University of Architecture and Technology as the research object. Based on linear relationship between the physical parameters and control parameters of the indoor environmental quality, the control and energy consumption optimization modeling is established, using the bilinear model according to the data measured. On this basis, the method of model predictive control is constructed and optimized by the ant colony algorithm. Experimental results show the effectiveness of the proposed approach.
    An Improved RFID Mutual Authentication Security Hardening Protocol
    TAN Feng
    2019, 26(4):  783-789. 
    Asbtract ( )  
    Related Articles | Metrics
    For the problem that the label information data is easily disclosed in LOT (Internet of Things), this paper proposes an improved RFID mutual authentication security hardening protocol. Unlike the traditional RFID authentication protocol, the proposed protocol authenticates the identity of members through authentication methods based on zero-knowledge proof, utilizes real-time information exchange between certifiers and verifiers to complete the zero-knowledge proof, and programs the participants’ identity security to their own identity key’s security. This protocol’ formal proof, including three aspects: secret proof, certification proof and label untraceability, shows that this protocol satisfies mutual authentication requirements of RFID.
    MPC Based Numerical Method for Fault-tolerant Control with I/O Constraints
    ZHANG Deng-feng, ZHANG Shen-peng, WANG Zhi-quan
    2019, 26(5):  971-977. 
    Asbtract ( )  
    Related Articles | Metrics
    For the sensor fault case of a class of discrete-time systems, the active fault-tolerant control is investigated in consideration of the control input and its rate constraints, as well as the measured output constraint. Based on the model-based predictive control (MPC) method and the constrained optimization algorithm, the design of the fault-tolerant controller is converted into the development of constrained convex optimization with the quadratic objective function. The fault-tolerant control input is then calculated online in recursive way by using the control input in the past time, the faulty sensor output and state estimation filter. Thus, a numerical fault-tolerant control method is derived based on the MPC strategy. The asymptotical stability of the closed-loop system is proved by improving the existing results in MPC. The input-output (I/O) constraints and the minimized quadratic performance are also guaranteed. Finally, simulations on the fault-tolerant control of an electronic throttle show the validity of the proposed method.
    Research on MPPT Strategy Based on Improved Area Different Method
    LI Xin, ZHANG Hong, WANG Rui-zhen, NI Xiao
    2019, 26(6):  1177-1182. 
    Asbtract ( )  
    Related Articles | Metrics
    The maximum power point tracking of photovoltaic cells is one of the key technologies of photovoltaic power generation system. The current control method of photovoltaic maximum power point tracking accuracy is not high, has the disadvantages of slow tracking speed and oscillation near the maximum power point resulting in energy loss, to overcome these shortcomings, an improved adaptive control strategy based on the method of area difference is proposed. Through the DC-DC transform circuit changing impedance to match the photovoltaic cell output impedance, and the use of the genetic algorithm in the harsh environment quickly and accurately track the maximum power point can be combined with the characteristics of stable work in the area of adaptive maximum power point difference method to achieve maximum power point tracking. The model is built on the MATLAB/SIMULINK simulation platform, and the results show that the improved adaptive area difference control strategy has the advantages of high tracking accuracy, fast tracking speed and smooth operation at the maximum power point.
    Fractional Order PID Sliding Mode Variable Structure Control based Inverter Circuits
    GUO Wei, WEI Miao, LI Tao, ZHOU Cheng-jie, WANG Xin
    2019, 26(7):  1397-1404. 
    Asbtract ( )  
    Related Articles | Metrics
    Voltage source inverter (VSI)-based higher-order circuits are widely applied in various industrial fields for their fast response and accurate control. The key to the successful application of the inverter is the steady-state performance, and the research focus is the control strategy. First, for one-to-four-order inverter circuit systems, the state space model is established in this paper, and then a novel sliding mode variable structure control strategy, fractional order PID sliding mode variable structure control algorithm, is introduced. And the simulation experiments show that the proposed fractional order PID sliding mode variable structure control has good control performance, such as, fast convergence rate, little tracking error and strong robust performance, so it has positive instruction significance for engineering practice.

    Dead-time Control of CNN DC Motor Based on Lyapunov Closed-loop Stability

    Zhang Jun-yong, Dong Fang, Miao Yi-fei
    2019, 26(8):  1515-1520. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at the problem of unknown parameters, dead-time input and non-linearity in traditional DC motor control strategy, a dead-time control strategy of DC motor based on Lyapunov closed-loop stability Convolutional Neural Network (CNN) is proposed. Firstly, the dynamic system model of DC motor and the control objective of adaptive convolution neural network are given. The unknown parameters of DC motor system are approximated by convolution neural network, and the Lyapunov function is used to design the state feedback adaptive controller. Then, the signal definition in closed-loop control system is given. Its stability is analyzed theoretically. Finally, the proposed control strategy is modeled and simulated by using MATLAB platform. The results show that the proposed algorithm has good control characteristics.
    Research on Control of Digital Hydraulic Cylinder Based on Disturbance Observer#br#
    #br#
    WANG Hui, JIANG Shou-Ling
    2019, 26(9):  1776-1781. 
    Asbtract ( )  
    Related Articles | Metrics
    There are various kinds of disturbances in the digital hydraulic cylinder, including uncertain parameters and uncertain nonlinearity. These factors will limit the high precision position control of the digital hydraulic cylinder. Aiming at high precision position control of digital hydraulic cylinder, a control strategy combining backstepping control with nonlinear disturbance observer is proposed to improve the tracking accuracy of position control. Firstly, the nonlinear control model of the digital hydraulic cylinder is established. Based on Lyapunov method, the designed system controller can guarantee the global stability of the system. Finally, the effectiveness of the control strategy is verified by MATLAB/Simulink simulation software. Simulation results show that the control strategy can effectively reduce the position tracking error, phase lag, steady-state limit cycle and low-speed crawling caused by uncertain parameters and uncertain nonlinearity. At the same time, it can improve the response speed of the system, make the system more robust and improve the position tracking quality.
    Research on Smelting and Rolling Integrate Production Scheduling Based on SPC-EA Algorithms
    ZHANG Hao-yu, ZHANG Jian-xin
    2019, 26(10):  1960-1965. 
    Asbtract ( )  
    Related Articles | Metrics
    The production scheduling of steelmaking-casting-hot rolling (SM-CC-HR) integrate production is a class of complex job-shop scheduling problems. The integrated production process is described as a job-shop model in this paper. Based on the model, the active schedules encoding and decoding approaches for production scheduling processes are respectively proposed to improve the efficiency of integrate production. In order to avoid illegal chromosome and reserve the good characteristics of parent generation, an single parent crossover-evolution algorithm(SPC-EA)is presented. The simulation results show that the proposed SPC-EA can effectively deal with the job-shop scheduling problems with fast convergences and obtain the high quality solutions.

    Frequent Itemset Mining Using Prefix Tree in Big Data Environment

    HUANG Cai-juan, LIU Zhuo-hua, SUO Hui, YANG Bin
    2019, 26(11):  2136-2140. 
    Asbtract ( )  
    Related Articles | Metrics
     For the problems of low efficiency and scalability in frequent itemset mining, a new distributed FIM algorithm is proposed, and implements it on MapReduce framework. Firstly, the algorithm applies the idea of prefix sequence to construct a tree, by which all frequent itemsets can be found without exhaustive search over the transaction databases. Then, it produces frequent itemsets in a breadth-wide support-based approach. In each MapReduce iteration, the infrequent itemsets will be pruned away. It significantly deducts memory consumption and iteration time of each MapReduce job. Finally, the experimental comparison with different algorithms is performed under different scales of business and support degree. The results show the good efficiency and scalability of sequence-growth especially for dealing with big data and long itemsets.

    A Capacity Increasing Method of Using SAA for Wireless Mesh Network

    HE Jian, HU Yan, WEI Yu-ke
    2019, 26(12):  2401-2406. 
    Asbtract ( )  
    Related Articles | Metrics
     In order to improve the capacity of wireless Mesh networks without adding network nodes and gateways, a capacity increase method based on simulated annealing algorithm (SAA) and integer linear programming (ILP) model is proposed. First, the topology of a single RF single channel wireless mesh network is modeled as a directed graph. Then, considering the interference constraint, the capacity increase problem is constructed as an ILP model, and the simulated annealing algorithm is used to quickly select the link that can increase the capacity. Finally, the ILP model is used to increase the capacity of these links to maximize the total network throughput. The simulation results show that the proposed method can effectively improve the network throughput and can find the optimal solution in a short time.
    Smart Energy Cloud Platform Based on MQTT and ILZ4 Compression Algorithm#br#
    #br#
    LU A-li, GU De-lin, ZHANG Jian-shu, HUO Ying
    2020, 27(1):  174-181. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to adapt to the smart energy application with large-scale data and fast response requirement, a smart energy cloud platform based on MQTT message transmission and ILZ4 algorithm is proposed. message queuing telemetry transport (MQTT) protocol is introduced into the data communication between Internet of things (IoT) and the cloud platform. The message queue architecture and uploading/downloading message flow process via the MQTT protocol are designed, and the ILZ4 compressor can be introduced and integrated into the tasks of information storage and message transport to achieve real-time data compression and transmission of large-scale monitoring flow. Three million monitored data points are recorded as input data stream of the cloud server. The experimental results show that, the proposed method gets better performance in compression ratio and throughputs, which can quickly reduce the storage cost and transmission overhead of large-scale data. So the proposed platform can provide a good, universal and scalable solution for smart energy applications.
    Moving Tracking Algorithm Based on Minimum Sigma Point Slope with Unscented Particle Reconstruction Filter
    LIU Hong-qing, LIU Yan, SHU di-qing, ZOU zhi-xian
    2019, 26(2):  355-361. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the tracking accuracy of the moving object, a moving object tracking algorithm based on the minimum Sigma point slope particle reconstruction filter is proposed. Firstly, we use the split and merge tracker to solve the complex tracking problem under uncertain environment target tracking, the multi direction can be different from the position of the target parallel tracking, which could reduce the loss probability; Secondly, in order to reduce the computational burden due to the unscented particle filter Sigma point aggregation degree, we use the minimum Sigma point slope to improve the trace particle filter algorithm for the fission of sub trackers, which could improve the computational efficiency of the trace particle filter algorithm. Finally, the experimental results show that compared to the several selected location methods, the proposed tracking method can obtain better positioning effect at lower cost, and can balance the network load and improve the detectability of the lifetime of the sensor network.
    The Selection of Data Product Service Provider Based on the Single-valued Neutrosophic Model
    2020, 27(02):  391-395. 
    Asbtract ( )  
    Related Articles | Metrics
    For the single-valued neutrosophic multi-attribute decision making (MADM) problems that the attribute weights are completely unknown, a novel MADM method is developed on the basis of single-valued neutrosophic entropy. First, a new axiomatic definition of single-valued neutrosophic entropy is introduced. Then, by using the cosine function, a single-valued neutrosophic information entropy formula is constructed to measure the uncertainty of SVNV, and it is proved that the constructed formula satisfies the four axiomatic requirements of single-valued neutrosophic entropy. In addition, a programming model is proposed to determine optimal attribute weights with the principle of minimum uncertain information, and a single-valued neutrosophic MADM method is investigated that the attribute weights are completely unknown. In the end, a numerical example of selection for data product service provider is provided, and the rationality and effectiveness of the developed method are certified by comparing with the existing method.
    Predictive Control Based on State Space Multivariable Error Correction
    WANG Li-jun, MENG Ying-jun, LUO Wei, ZHOU Yue-e
    2019, 26(3):  578-583. 
    Asbtract ( )  
    Related Articles | Metrics
    The control of distillation column is commonly used in industrial equipment in the petrochemical industry, if there is a big tower parameter disturbance, the control mode of the traditional PID is not ideal in the control effect, but the application effect of the complete form of the multivariable decoupling model is not ideal, because the matching of the control model is not ideal, there is a problem that the parameters do not match the actual application. In this regard, the state space multivariable predictive control method is introduced, and the traditional PID control strategy is combined with the design of the distillation tower controller. Because of the combination of the advantages of the PID controller and the state space multivariable control method, the algorithm studied can effectively improve the control precision and response speed of the distillation tower, and effectively suppress the oscillation problem during the distillation operation. The experimental analysis shows that the proposed algorithm has a better control effect in the control process of the distillation column, and the effectiveness of the algorithm is verified.
    Research on the Dephosphorization Ladle Scheduling algorithm of Steelmaking-refining-continuous Casting Process
    LIU Wei, PANG Xin-fu, CHAI Tian-you
    2019, 26(4):  790-798. 
    Asbtract ( )  
    Related Articles | Metrics
    At present, the steel plant adopts the manual method to carry out the ladle scheduling, the optimization results of the ladles selection are not good enough because of the uncertainty of ladle temperature, ladle life and ladle materials. Ladle scheduling is to select and distribute the ladles based on the heat plan, providing that the process time of heats and the process requirement of the dephosphorization for heats are given. The selection of dephosphorization ladle takes the performance index of maximum temperature, highest life, and the remaining online ladle life. Take the ladle temperature in the specified range, the ladle life within the specified range and the ladle maintenance end time as early as the furnace processing time as the constraints to determine the dephosphorization. This paper adopts consistency classification method to obtain the dephosphorization ladle rule, and use the rule-based reasoning to get dephosphorization ladle. The performance is tested by simulation experiments. The experimental results show that, compared with the manual scheduling, the algorithm enables the production work well and improve the production efficiency, and improve the economic efficiency of enterprises.
    A Hybrid Digital Rotation Coordinate Positioning Algorithm Based on DSP
    HU Xiao-fang
    2019, 26(5):  978-983. 
    Asbtract ( )  
    Related Articles | Metrics
     The solution of high precision phase belongs to an important part of the femtosecond laser tracker measurement system, in order to meet the requirements of phase precision in fixed-point DSP, the coordinate rotational digital computer (CORDIC) algorithm are studied. Based on the traditional CORDIC algorithm anyway, the mixed radix algorithm is proposed and its feasibility is verified. Two algorithms are realized on TMS320VC5402 and the performance of both are compared. The research shows that the hybrid algorithm can not only obtain the same accuracy as the traditional algorithm, and also can reduce the running time and hardware cost of the program.
    The Robust Selecting Weight Iteration Algorithm Application in Attitude Measurement
    HE Hong-li, ZUO Yi-hong, LI Hong
    2019, 26(6):  1183-1186. 
    Asbtract ( )  
    Related Articles | Metrics
    It becomes more difficult to precisely align the radar array with the reference mounting surface of plane as the decrease of radar antenna array. A complete measurement scheme is given and a measurement system is constructed to solving the attitude measurement of small antenna array surface that installed on the airplane. According to the measurement data with gross error, a robust selecting weight iteration algorithm with initial value is proposed on the fundamental theory of tolerance estimation. The accuracy of the algorithm is verified, and the processing results are satisfactory. The algorithm has been successfully applied to the position measurement of airborne radar antenna array, and it can also be widely used in the installation and calibration of other weapon systems.
    Design of a kind of Fault Diagnosis Observer in Nonlinear System
    WEN Xiu-ping, CHEN Wei, FU Xiao-yan, ZHANG Jun
    2019, 26(7):  1405-1412. 
    Asbtract ( )  
    Related Articles | Metrics
    To study the design of a kind of fault diagnosis observer in nonlinear system, the fault diagnosis observer is designed according to the faults of actuator and sensor in the same nonlinear system. The stable and sufficient conditions of fault closed-loop system that is able to meet certain performance indicators are made using linear matrix inequality approach. Finally, a numerical example is used to verify the effectiveness of the proposed fault diagnosis observer, and the simulation results show that the fault diagnosis observer can diagnose the system faults well.
    Quality Inspection Method for Integrated Circuit Packaging Product Based on Image Processing
    FAN Hai-dong, CHEN Xuan-hong, LUO Sheng-wei, LI Qing-yi, ZHAO Chun-hui
    2019, 26(8):  1592-1598. 
    Asbtract ( )  
    Related Articles | Metrics
    The IC packaging process is a vital process in the IC manufacturing industry. The quality of the package directly affects the reliability and service life of the finished chip, which in turn limits the overall performance of the electronic product. In order to monitor and guarantee the package quality of the chip during the production process, it is essential to measure the package quality of the integrated circuit. This work starts with the process characteristics of the packaging process and proposes an automatic detection and calculation method for packaging flash based on image processing methods. The method realizes the quantitative measurement of package flash, which is of great significance for the quality closed-loop control of the integrated circuit packaging process.
    Control Modeling and Fault Simulation Analysis of IBDGs in Microgrid
    YANG Yi, LU Tian-qi, YU Chang-yong, et al
    2019, 26(9):  1782-1788. 
    Asbtract ( )  
    Related Articles | Metrics
    The microgrid contains a large number of inverter based distributed generators (IBDGs), whose operation control and fault characteristics are different from that of traditional synchronous generators. The inverter control mode of IBDG is analyzed. The simulation models of different operation control modes (grid-connected operation and islanding operation) of IBDG in the microgrid are established on the DIgSILENT simulation software. The fault characteristics of both IBDG side and distribution line side, and the influences on the fault protection under different operation control modes are analyzed and compared, which provides the basis for the protection strategy of the distributed power microgrid.
    Research on the Matrix Information Aggregation Method Based on the Firefly Algorithm
    ZHANG Lei
    2019, 26(10):  1966-1970. 
    Asbtract ( )  
    Related Articles | Metrics
    Because of the universality and importance of group decision making, the research of the judgment matrix aggregation method is an important issue of the group decision making, which is becoming more and more widely and deeply. First, in view of the diversity of the judgment matrix in the group decision making, the glowworm swarm optimization is used to solve the matrix aggregation. Then, the introduction of the consistency ratio in the objective function of the glowworm swarm optimization can reduce the subjectivity and information loss of the aggregation process. Finally, through the concrete empirical research, the improved algorithm can provide an effective and relatively uniform method for judgment matrix aggregation in group decision making.

    Hierarchical Model Predictive Control Strategy Based on Model Switching Considering Economic Benefits

    WANG Ni, AN Ai-min
    2019, 26(11):  2141-2146. 
    Asbtract ( )  
    Related Articles | Metrics
    Hierarchical model predictive control(HMPC) strategy based on model switching is proposed to solve the problem of optimal working point deviation calculated by plant-wide optimization. In the plant-wide optimization layer, SQP algorithm is used to calculate the optimal point under maximize economic benefits. In the control layer, the whole workspace is divided into several subintervals, in the subintervals the corresponding sub models are set up with the minimum gain method, last MPC (model predictive control) controller is designed under sub model selected by output error index to track the optimal point. In a word, HMPC strategy based on mode switching can realize system optimization in the economic and control performance, and the comprehensive economic benefits of the system is improved. In this paper, simulations show that HMPC strategy based on model switching is effective in improving economic benefits. The comparison between the multi-model control strategy and the single model control strategy show that the system control performance is improved by HMPC strategy based on model switching.

    Control and Optimization of Semi-active Seat Suspension Based on Inerter

    ZHAO Qiang, ZHANG Na, YUE Yong-heng
    2019, 26(12):  2309-2314. 
    Asbtract ( )  
    Related Articles | Metrics

    Dual-layer vibration isolation has good vibration attenuation effect, but its application in vehicle aggravates the vehicle load additionally. To solve this problem, this paper replaces the intermediate mass of dual-layer vibration isolation with Inerter, and further applies it into vehicle seat suspension. This paper first proposed a new seat suspension structure including magneto-rheological damper and Inerter, and derived the seat-human body motion differential equations. Based on these equations this paper presented a model-based (based on seat suspension dynamics model) control scheme, established the corresponding Simulink model, and optimized the parameters of both the seat structure and its controller with the Free-Search (FS) algorithm. This paper further completed the simulation tests using a compound excitation of three frequencies where the driver is easy to resonate，as well as a random excitation. These tests show that the proposed seat structure and controller parameters have better vibration attenuation effect.

    Hesitant Fuzzy Kernel C-Means Clustering for Database System Selection
    DENG Xiao-yan
    2020, 27(1):  182-187. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to deal with clustering problems for hesitant fuzzy information, this paper normally solves them on sample space by using a certain hesitant fuzzy clustering algorithm, which is usually time-consuming or generates inaccurate clustering results. To overcome the issue, we propose a novel hesitant fuzzy clustering algorithm called hesitant fuzzy kernel C-means clustering(HFKCM) algorithm by means of kernel functions, which maps the data from the sample space to a high-dimensional feature space. As a result, the proposed HFKCM algorithm expands the differences between different samples, and makes the clustering results much more accurate. Finally, by conducting simulation experiments on the selection of database systems, and the results reveal the feasibility and availability of the proposed hesitant fuzzy kernel C-means clustering algorithm.
    Research on Load Power Prediction Model of Hybrid Power Ship
    GAO Di-ju, PAN Kang-kai, WANG Tian-zhen
    2019, 26(2):  362-367. 
    Asbtract ( )  
    Related Articles | Metrics
    The short term prediction model of chaotic time series based on multi-resolution wavelet neural network (MRA-WNN) is set up to realize the optimal power allocation between the power sources of the hybrid power ship. The wavelet function and the scaling function are used as the network basis function. First, the overall profile of the time series is approximated in a large scale. And then, according to the different degrees of load power fluctuation, the approximation of the layer by layer is added to the details for improving the prediction accuracy. The translation and scaling parameters of wavelet basis functions are determined by the multi-resolution solution, and the number of training parameters can be decreased and the calculation speed can be improved by combining the multi-resolution analysis learning algorithm. The experimental results show that the MRA-WNN has high prediction accuracy, and it is an effective method for the prediction of the load power of hybrid power ships.
    The Selection Model of Database Based on the Interval-valued Normal Information Aggregation Algorithm
    ZHOU Tian-qi, LIU Meng
    2020, 27(02):  396-401. 
    Asbtract ( )  
    Related Articles | Metrics
    For the multi-attribute decision-making (MADM) problems that the attribute weights are completely unknown under the interval-valued normal fuzzy environment, two interval-valued normal fuzzy information aggregation algorithms are designed, a novel interval-valued normal fuzzy MADM model is investigated. First, the interval-valued normal fuzzy operational laws are defined. Then, from the arithmetical and geometric point of view, the interval-valued normal fuzzy weighted averaging operator (IVNFWA) and interval-valued normal fuzzy weighted geometric operator (IVNFWG) are proposed. The relationship between these two operators is analyzed. Finally, combining these two proposed operators with distances, a new model is developed to deal with the interval-valued normal fuzzy MADM problems in which the attribute weights are completely unknown, and then apply the developed model to research on the selection of database system. The results obtained from performance analysis show that the proposed approach is correct, feasible and efficient.
    Design of Diagnostic Expert System for Launch Vehicles Based on FTA
    PENG Hua-liang, SHEN Shu-long, LI Jun, ZHOU Chen-cheng
    2019, 26(3):  584-588. 
    Asbtract ( )  
    Related Articles | Metrics
    It is difficult to locate and analyze the fault by the traditional method as the structure of launch vehicles is complex and the fault mode is various. On the basis of the research of the launch vehicle system, an information fusion system for the fusion of multi-channel fault symptoms and a knowledge base system are designed. A fault diagnosis method based on fault tree is put forward, and a fault diagnosis platform for launch vehicles is developed. The reasoning machine of the system is mainly composed of rule reasoning and FTA, and the process of reasoning has been realized. Experimental results show that the fault diagnosis method can effectively diagnose the fault of the launch vehicle, and it has strong adaptability to different systems.
    Design of Central Control Mode of Handling Manipulator for Punching with MP2300S
    LI Shang-rong, WANG Ke-sheng, LI Xing-cheng
    2019, 26(5):  984-990. 
    Asbtract ( )  
    Related Articles | Metrics
    Robots replacing people is an effective way of traditional stamping production industry technology upgrading. The design of four degrees of freedom moving manipulator with controller MP2300S is presented. The manipulator is composed of four moving parts, such as a rotational base, a moving vertically upper arm, a stretching horizontally forearm and a rotating gripper, each of which is actuated by AC servo motor. The centralized control mode that a multi-axis motion controller could control dozens of different robots whose axises are driven by AC servo motors is achieved. The results of test show that the robot could move quickly and smoothly from one place to another in the range of motion. The maximum period of the operation time is no more than 8 second per piece and the repeat positioning accuracy is 0.1 mm.
    Fuzzy Control of Nonlinear Time-delay Systems Based on T-S Model
    QI Shu-nan, ZHOU Kun, HUANG Tian-min
    2019, 26(6):  1187-1191. 
    Asbtract ( )  
    Related Articles | Metrics
    The problems of stability analysis and control design for nonlinear time-delay systems represented by a (Takagi-Sugeno, T-S) fuzzy model are investigated. Firstly, a novel integral inequality is chosen to dispose the integral term in the derivative of the Lyapunov-Krasovskii functional, and then the less conservative delay-dependent stability conditions are obtained. Secondly, combining with Finsler lemma, a fuzzy state feedback controller design strategy by means of linear matrix inequalities (LMIs) is presented under the parallel distributed compensation (PDC) technique. Finally, two numerical examples are given to show the effectiveness of the presented stability analysis and control strategy.
    Inverse Control of Permanent Magnet Synchronous Motor Based on ESO Self Anti-Perturbation
    BIAN Jiang, NIU Cong , YAO Jia-chen
    2019, 26(7):  1413-1418. 
    Asbtract ( )  
    Related Articles | Metrics
     In order to effectively solve the influence of the internal and external disturbance of the permanent magnet synchronous motor on the control system, and improve the self anti-perturbation ability of the control system. An adaptive inverse system synthesis control algorithm based on extended state observer (ESO) compensation is proposed. The second-order extended state observer (ESO1) of d axis current system and the third-order extended state observer (ESO2) of the speed control system are designed for real-time estimation of the uncertain disturbance and unknown state of the speed control system, and use it to do feedforward compensation. The stator resistance and inductance parameters of the motor are identified by model reference adaptation. The experimental results show that the proposed algorithm has strong robustness to the internal parameters perturbation and external load disturbance of the motor.

    Study on the Calculation Method of ω Input Signal in PSS4B Model

    LI Song
    2019, 26(11):  2147-2151. 
    Asbtract ( )  
    Related Articles | Metrics
     A study on the calculation method of speed input signal in PSS4B model is proposed. The method has less computation and is easy to realize in the excitation regulator. It provides a simple and effective way to implement PSS4B on the generator excitation regulator. Through the RTDS platform to build the model test, the effect of PSS4B on low frequency oscillation in three bands of high, medium and low frequency are compared. The results show that the PSS4B of speed input signal of the algorithm has obvious inhibition effect on the oscillation of each frequency band.
    Research and Realization of Synchronous Robotic Arm with Autonomous Path Planning Functions#br#
    #br#
    2020, 27(1):  188-193. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to solve the problem that elderly or patients in bed are unattended and improve their self-care ability, a synchronous robot arm with autonomous path planning is proposed. The user specifies the moving robotic arm to reach the destination through a mobile phone APP, and then guides the robot arm to perform the body arm behavior synchronously through a synchronization device on the arm such as object grasp. The system adopts RFID location systems with dense passive tags to arrange a 4*4m2 RFID tag array indoors, and paths planning based on fuzzy logic. Experimental results show that the system is capable of helping a user to grasp ninety present of objects in daily life.
    Network Filter Design for Continuous-time Systems Using a Novel Event-triggered Scheme
    LI Jin-shuo
    2019, 26(2):  368-372. 
    Asbtract ( )  
    Related Articles | Metrics
    For the purpose of improving the usage of network bandwidth, and let the network filter be robust to packet drops happening during information transmission, a new algorithm of sampled event-triggered filter is proposed. Firstly, the structure of the network filter and triggered law is designed based on careful analysis of the nature of network environment. Secondly, utilizing the modeling method in the sampled-tine control system, the filter error system is modeled as a time-varying delay system with known bound. Using the Lyapunov-Krasovski method, a new sufficient condition for the existence of a H∞ filter is given in the form of LMI. Finally, we give a simulation experiment to demonstrate the effectiveness of the proposed algorithm. The simulation results show that, compared with the traditional sampled-data filter, the proposed filter not only guarantees the H∞ performance of the estimation error systems, reduces the traffic jam, but also has robustness of packet drops induced by the network environment.
    Simulation and Experimental Research on Sensorless Control of SPMSM
    XU Ming-qing, SUN Dian-sheng
    2020, 27(02):  402-408. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the performance of position sensorless control system of surface mounted permanent magnet synchronous motor (SPMSM), the extended state observer is applied to sensorless control of surface-mounted permanent magnet synchronous motor to estimate the rotor position angle and speed. It is proposed to estimate the rotor position by constructing an extended state observer with stator current as the main variable in two-phase stationary coordinate system and observing the armature back-EMF. An extended state observer with estimated rotor position angle as the main variable is constructed for speed estimation. This method has high accuracy of rotor position angle and speed estimation when the resistance and inductance parameters of the motor change. It is suitable for middle and high speed sensorless control of surface-mounted permanent magnet synchronous motor. The simulation and experimental results show the effectiveness of the proposed method.

    GNB Classification and Detection of Data Streams Based on Weighted Mechanism Concept Drift

    LIU Hong-qing, SHU Di-qing, LIU Yan, HUANG Yan
    2019, 26(3):  589-596. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the accuracy and efficiency of data flow classification detection, a new Gauss naive Bayes classification method based on weighted mechanism concept drift detection is proposed. Firstly, the proposed algorithm framework is designed, and the input data stream is used to establish the information table directly, and the Gauss naive Bayes classifier based on the information table is also constructed; Secondly, the Kappa statistical method is used to establish the concept drift detection method. According to the input data fluctuation, linear function and Bias function (nonlinear) are taken to detect the concept drift, and expert point deletion and information table are used to deal with the recurrent concept drift, to improve the drift detection accuracy and efficiency; Finally, simulation experiments show that the classification accuracy on the SEA test set, Hyperplane data set and SQD data set is 10.3 %, 16.8 % and 20.5 % higher than that of the contrast algorithm, which verifies the effectiveness of the classification algorithm.
    Research on Knapsack Problem Based on the Hybrid Algorithm of Particle Swarm Optimization and Simulated Annealing
    GENG Ya, WU Fang-sheng
    2019, 26(5):  991-996. 
    Asbtract ( )  
    Related Articles | Metrics
    A hybrid algorithm of particle swarm optimization and simulated annealing based on intuitionistic fuzzy entropy (IFEPSO-SA) is proposed for solving the classical knapsack problems. In order to keep the diversity of population, an inertia weight of dynamic changes and mutation operation are built in the algorithm by using a metric based on intuitionistic fuzzy entropy (IFE) of the population. Furthermore, the partial best-solution of PSO is updated by using an exchange operation and a simulated annealing mechanism to get the better partial best-solution and global best-solution, and increase the searching ability. The experimental results show that the algorithm has better robustness and searching ability, and is useful of dealing with 0-1 knapsack problem.
    Seam Tracking Control of Robot Based on Fractional-order   Control
    ZHANG Yao, LIU Shu-qing, SHENG Guo-liang, LIU Xin
    2019, 26(6):  1192-1196. 
    Asbtract ( )  
    Related Articles | Metrics
     In order to improve the seam tracking control performance of the robot，a design approach of fractional-order  controller is proposed. Firstly, According to the principle of the fractional-order, the fractional-order  controller was designed. Secondly, hybrid particle swarm optimization (HPSO) was used to tune fractional-order  controller parameters. This algorithm is on the basis of particle swarm optimization (PSO) and combines the characteristics of genetic algorithm crossover and mutation，which improves the global search ability. The function based on integral of time-weighted absolute error (ITAE) is served as optimization objective, and the multiple signals of the system are simulated. The simulation shows that the fractional-order  controller has a fast convergence speed, good control effect and can achieve the anticipative effect.
    Control Algorithm with Neutral Point Potential of Three-level APF
    LIAN Han
    2019, 26(7):  1419-1424. 
    Asbtract ( )  
    Related Articles | Metrics
     An improved algorithm is proposed that mainly focused on neutral point potential balance control of the diode clamped three-level active power filter in this paper. Firstly, this paper describes the cause of neutral point potential fluctuation in DC-side of three-level active power filter, and analyzes the control principles. In actual work, the main circuit state of active power filter is often required to switch between the rectifier and inverter, so it is difficult to determine the appropriate balance factor. This paper conducts a thorough study, and takes the fuzzy control method to solve this problem. The study found that the problem was solved by introducing fuzzy control into the balance control of the midpoint potential. Finally, the effectiveness of this method is verified by simulation and experimental results.

    Adaptive Control of Microgrid Power Balance Based on Network State Estimation

    ZHU Yi-xian, LIU Lu-deng, CHEN Cun-lin, ZHANG Wei, WANG Yuan-yue, LI Miao, YE Hai-feng
    2019, 26(11):  2152-2158. 
    Asbtract ( )  
    Related Articles | Metrics
     In order to realize the effectiveness of adaptive control for microgrid power balance, an adaptive power balance control method based on network state estimation is proposed. The algorithm takes full account of traffic congestion / non congestion performance, and uses real-time network state estimation combined with gain scheduling technology to make the controller adapt to the change of communication network state. Then, the moving average threshold estimator is adopted, and the buffer length and threshold selection method are provided in the case of congestion/non congestion in two PLC communication networks. In addition, a consensus based multi agent control system design procedure is developed, which ensures that all evaluation states converge to reference state values, so as to ensure the fairness of assessment state participation. Finally, simulation results show the effectiveness of the proposed algorithm.
    Multivariate Process Variables Abnormal Data Segments Detection Based on Correlation Coefficient
    PANG Xiang-kun, HUANG Yue, WANG Zhen, YU Yan, GAO Song
    2020, 27(1):  194-200. 
    Asbtract ( )  
    Related Articles | Metrics
    The historical normal and abnormal data sets of process variables are premises of assessing and optimizing alarm performance and designing dynamic alarm trip-points of industrial alarm system. This paper proposes an improved abnormal data detection method, which is based on the correlation coefficients between process variables. The main idea is to divide multivariate time series of process variables on the basis of correlation coefficient values and suitable length of data segments, obtain the mutual variation directions of process variables through Spearman rank correlation coefficient and corresponding hypothesis test, and detect abnormal data segments that have inconsistent variation directions with prior knowledge for normal conditions. Simulation examples and industrial case are provided to validate this method.
    Co-design of Control and Communication Based on Event-triggered Scheme for Networked Control Systems
    WANG Zhi-wen, ZHAO Ying
    2019, 26(2):  373-378. 
    Asbtract ( )  
    Related Articles | Metrics
    Considering the coupled problems of communication network and control systems for network control systems, co-design of control and communication based on event-triggered scheme for network control systems is studied. First, the model of event-triggered control based on the communication network is built, by analysing the model of control systems and congestion control of the communication network, a novel event-triggered condition is presented. And then, by applying the Lyapunov-Krasovskii functional approach and linear matrix inequality, the performance of network control systems are analyzed, and the controller are designed. Finally, a numerical example shows the correctness of this conclusion.
    A Dynamic Distance Estimation Method for Multi-mode Speed Mobile Nodes
    QIN Ning-ning, ZHU Shu-cai
    2019, 26(3):  596-601. 
    Asbtract ( )  
    Related Articles | Metrics
    The uncertainty of the moving speed of the target nodes in the sensor network, brings a serious challenge for dynamic ranging. An improved dynamic RSSI-based distance estimation method is proposed, which utilizes pattern matching in term of the sliding window. By measuring the received signal strength indicator in the communication process of nodes, the mapping relation between the received signal strength indicator and time is analyzed and determined. The linear treatment for the real-time RSSI data streams obtained is produced in the moving process. The sliding window pattern matching is used to realize high precision dynamic distance estimation for multi-mode speed mobile nodes, which contains uniform, uniform variable and variable acceleration nodes. The experimental test shows that the method can overcome the uncertainty of RSSI data, and can realize the dynamic distance estimate error for multi-mode speed mobile nodes less than 2.6% at the same time.
    Algorithm of Fog Removal of Image Based on Improved Kuwahara Filter
    WEN Li-min, JU Yong-feng, ZHANG Chang-li, WANG Hui-feng
    2019, 26(5):  997-1002. 
    Asbtract ( )  
    Related Articles | Metrics
    Concerning the shortcoming of low efficiency of the algorithm for single-image fog removal, an algorithm based on improved Kuwahara filter is proposed to detail rough transmission of foggy images. This algorithm introduces the square integral operator to transform calculation for pixel areas into calculation of four vertices of a rectangle. Amended algorithm based on threshold for transmission is used to go a step further detail the transmission for sky areas in order to increase the efficiency of the algorithm and avoid the color-cross of sky areas. Simulation test shows that it only needs 10 ms to deal with a foggy image of 800×600 pixel, and the velocity based on the improved Kuwahara is 3 000 times of He’s, 2 000 times of Shi’s, and could meet the real-time processing need for expressway images.
    A Model Study of the Existence of Relationship Among Input Variables in Group Decision Making
    ZHAO Yan-ping
    2019, 26(6):  1197-1203. 
    Asbtract ( )  
    Related Articles | Metrics
    An improved triangular hesitant fuzzy multi-attribute decision-making model is proposed to solve the decision-making problem in which the attribute evaluation information is intrinsically related and the attribute value is triangular hesitant fuzzy element. Firstly, the basic operation rule of triangular hesitant fuzzy Einstein is defined by combining Einstein operation. Based on this rule, the trigonometric hesitant fuzzy weighted average (THFEWA) operator and the trigonometric hesitant fuzzy weighted geometric (THFEWG) operator are defined. Secondly, a trigonometric hesitant fuzzy model for multi-attribute decision making is developed based on the above two new operators. Finally, the proposed model is applied to evaluate the comprehensive performance of multimedia equipment. The experimental results show that the proposed decision-making model is feasible, more effective, and has certain application value.
    Sensor Fault Diagnosis and Identification Method Using Adaptive Particle Filter
    LIU Hong-yan, MAI Yan-hong, KONG Fan-nie, MU San-min
    2019, 26(7):  1425-1430. 
    Asbtract ( )  
    Related Articles | Metrics

    In the general stochastic nonlinear and non-Gaussian systems, the sensor faults including biased and scaled readings caused by sudden calibration errors have adverse effect on the precise monitor and stable control of the system. To deal with this problem, a novel diagnosis and identification method is proposed. An adaptive particle filter is developed to calculate the difference between the measurements and the particle filter estimates, then the type and magnitude of sensor faults are determined through with maximum likelihood estimation, thus the fast and precise detection of sensor fault is realized, and the adverse effect caused by the faults can be compensated. Some simulations are carried out on a boiler model, and the results validate the effectiveness of the proposed method.

    Topology Verification of Low Voltage Distribution Network Based on ROF Outliers Detection Algorithm
    GUO Shen, LIN Jia-ying, WANG Peng, ZHANG Ji-chuan, CHEN Lei, TANG Guo-jing
    2020, 27(1):  201-206. 
    Asbtract ( )  
    Related Articles | Metrics
    In the existing verification methods of low-voltage distribution network topology, most of smart meter voltage sequence data of customers in the most recent period of time are extracted from the Advanced Metering Infrastructure (AMI), and the correlation between the voltage sequence data is calculated to measure the similarity between voltage sequence profiles of different customers. However, the existing Local Outlier Factor (LOF) detection algorithm cannot detect the outliers. Therefore, a low-voltage distribution network topology verification algorithm based on ring outliers factor (ROF) detection algorithm is proposed in this paper. ROF algorithm verifies the customer with inaccurate connection of the transformer by correlation coefficient of voltage sequence data, and analyzes the degree of abnormality in the customer's ring domain, which can effectively verify the topology connection between the customer and the transformer in the GIS system.
    Research on Fresh Logistics Monitoring System Based on Compressive Sensing
    GENG Xiang-hua, WANG Gui-feng
    2019, 26(2):  379-385. 
    Asbtract ( )  
    Related Articles | Metrics
    The monitor system of the fresh logistics transportation system based on wireless sensor networks enables the real-time tracking and quality control of products. The traditional monitoring system needs to transmit the sensor data to the control center in real-time and it would cause the overload of data links and communication systems and reduction of data acquisition and transmission efficiency. This study aims to design a wireless sensor network monitoring system of fresh logistics transportation. By using the compressed sensing technology, the data sampling rate is reduced effectively to reduce the system pressure. Test results show that this system can accurately and efficiently recover the data collected by sensors and feedback the goods temperature variation throughout the fresh logistics in real-time to provide effective regulation and the security guarantee for the transport of goods.
    Compound Bayesian Network Retrieval Model Based on Semantic Extension
    BAI Yan-xia, CHENG Jie, MO De-ju
    2019, 26(3):  602-607. 
    Asbtract ( )  
    Related Articles | Metrics
    One of the most important reasons that affect the information retrieval result is the phenomenon of semantic match of user query and the document while syntactic mismatch. Capturing synonym relationships to extend the query term and combining the retrieval result of the simple Bayesian network retrieval model, a compound Bayesian network retrieval model is proposed. The internet topology of the compound model, the retrieval process and the corresponding retrieval algorithms are given. Experimental results show that the model can realize the semantic retrieval, and further optimize the retrieval performance.
    Risk Identification of Electricity Market Operation Management Based on Fuzzy-Delphi and HFLTS-AHP Methods
    LI Zhi-feng, SHI Hang, WU Jing-ying, WANG Miao, WANG Dong-xue
    2019, 26(5):  1003-1010. 
    Asbtract ( )  
    Related Articles | Metrics
     Since the publication of electricity reform No. 9, the construction of electric power market has been advanced continuously in our country. The article studies the operation and management of the electricity market from the perspective of risk, and identifies the importance of the operation and management risk of the electricity market. First, the Fuzzy-Delphi is used to screen the indicators of the operational risk of the electricity market and then the evaluation index model is established through HFLTS-AHP, and then the weights of 10 risk indicators are obtained. The importance of the risk management of the electricity market is identified. Finally, the article proposes dynamic management recommendations for the prevention of the risk management of the electricity market. The analysis shows that the imperfect risk level of the market-related system is low and in a controllable state. The risk assessment model points out that the two indicators of “legal and regulatory risks” and “management committee operational effectiveness risks” are at a high risk, and should pay close attention to the above two indicators in the process of functioning.
    The Mixed Multi-attribute Group Decision Making Method Based on Intuitionistic Fuzzy VIKOR
    CHEN Guo-luan, TIAN Sen-ping
    2019, 26(6):  1204-1210. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to solve the problem of group decision making problem with multiple attributes and mixed evaluation information, an evaluation method is proposed based on the intuitionistic fuzzy sets and VIOKR theory. First, the mixed attribute of different evaluation information is converted into intuitionistic fuzzy numbers, which can reduce the randomness and fuzziness of the evaluation information. Then, the minimum deviation optimization model is established to calculate the weight vectors of the experts and the attributes. In addition, the VIKOR theory is introduced to aggregate the evaluation values and rank the evaluation objects. The comparison with the TOPSIS method is presented to verify the feasibility and reliability of the proposed algorithm. Finally, the virtual training system of a certain type of power vehicle is used as research object and conduct the personnel business level decision-making, the results show that the group decision-making method can effectively realize the decision-making, and has a good engineering application value.
    Small Sample Expansion Method and Application Based on Data Distribution
    BI Lve, XIONG Wei-li
    2019, 26(7):  1431-1436. 
    Asbtract ( )  
    Related Articles | Metrics
    In the data-driven based soft sensor modeling procedure, the number of data samples has an apparent affect on the model accuracy. In the case of a small number of training samples, a method of data expansion combining Euclidean distance and angle principle is proposed. This method can determine the range of the sample expansion by analyzing the distribution characteristics of data, and the process information of modeling plant in each stage is improved by the extended data-set. By reconstructing the modeling data sets, the prediction performance of the model is improved. The simulation results of different industrial processes have indicated that the proposed method has good prediction accuracy and generalization performance in the case of less number of samples.
    Triangular Fuzzy Rules Based FANP Maintenance Decision Making for High Speed Railway Traction Power Supply System
    LIU Hang, LI Qun-zhan, ZHAO Yuan-zhe
    2019, 26(2):  386-392. 
    Asbtract ( )  
    Related Articles | Metrics
    In order to improve the accuracy of the decision making process of high speed railway traction power supply, and to ensure the scientific and reasonable maintenance decision weight assignment, a new method based on triangular fuzzy rule for FANP maintenance decision making of high speed railway traction power supply is proposed. Firstly, the triangular fuzzy rules of classical network analysis method is improved, according to the fuzzy preference programming method, the index weight of high speed rail traction power supply is determined, involving weights of criteria, weighted coupling and affiliated index weight; Secondly, for constraints and coupling relation indexes, according to the network structure, the weighted super matrix is constructed and dealt with in the random way to obtain the limit form of the super matrix, and then the weight of each index of comprehensive is obtained, candidate for the weight score to choose the best maintenance method. Finally, the simulation test indicates that the FANP algorithm is better than the traditional maintenance decision-making plan and standard hierarchical network (ANP) scheme in the limit relative grade, dominance index, maintenance cost and time. Sensitivity analysis results of the algorithm are given.
    A Weighted Probability Cluster Head Selection Algorithm Based on FCM Clustering for Wireless Sensor Network
    ZHAO Li-xin, DONG Chao-xian, ZHAO Li
    2019, 26(6):  1211-1215. 
    Asbtract ( )  
    Related Articles | Metrics
     Aiming at the problems of fast energy consumption and low lifetime of the traditional LEACH algorithm, a weighted probability cluster head selection algorithm based on FCM clustering for wireless sensor network routing protocol is proposed, which mainly optimizes the selection of cluster head. Firstly, the network was divided into several regions according to the location coordinates of the nodes by using FCM clustering algorithm. Assuming that WSN was consisted of heterogeneous nodes with different nodes' energy, the cluster head was selected by the concept of weighted probability according to different node types, at the same time, the cluster head nodes were distributed evenly. The simulation results show that the new algorithm has obviously improved the routing effect and prolonged network lifespan.
    Research on Improved Pulse Vibration of High Frequency Injection Method Based on Wavelet Transform
    SHI Wei-guo, YAN Xiao-yu
    2019, 26(6):  1216-1221. 
    Asbtract ( )  
    Related Articles | Metrics
    Aiming at the problem in accuracy of PMSM speed control system and position tracking that caused by the traditional high frequency signal injection method, an improved pulse vibration of high frequency injection method based on wavelet transform filter is proposed, which injects low amplitude and high frequency voltage signal in the d-axis. The multi-scale frequency band decomposition of the q-axis current signals containing the position information is carried out by using the db4 wavelet packet, the wavelet packet coefficient threshold is determined by the maximum and minimum criterion, and the position signal is effectively extracted by using the soft threshold selection method to reconstruct the decomposition factor of the wavelet packet. It can solve the problem of insufficient precision when extracting the low amplitude weak signal by the traditional Butterworth filter. The simulation results show that the proposed method can effectively eliminate the noise signal and extract position information. This method can ensure the accuracy of position tracking and greatly reduce the torque pulse vibration.
    Online quality-related fault detection of industrial processes based on SFA
    SUO Han-sheng, JIANG Bai-hua, GONG Xiang-yang, WANG Yong-yao, JIA Gui-jin
    2019, 26(6):  1222-1227. 
    Asbtract ( )  
    Related Articles | Metrics
    Considering the insufficiency of traditional monitoring methods to neglect dynamic information in the process industry, the study proposes a novel online feature reordering and feature selection based on slow feature analysis algorithm (improved FROSSFA), which can expand the SFA fault detection method to the field of quality-related fault detection. Finally, the proposed method is utilized in the process of Tenness-Eastman, and the results show that the improved FROSSFA method has higher fault detection rate, and it can determine whether the fault is related to the quality accurately.
    Fuzzy PID Control System for Liquid Drip Speed Based on MSP430
    GUO Xia, ZHANG Qian, TAN Ya-li
    2019, 26(6):  1228-1232. 
    Asbtract ( )  
    Related Articles | Metrics
    Doctors usually cure patients by intravenous infusion, according to the type of drug and the patient's specific illness, The appropriate infusion rate has a great impact on treatment of disease and patient safety. Based on the MCU MSP430 and the application of photoelectric sensor, a set of liquid drip speed fuzzy PID control system has been designed to set the injection speed of the liquid drip according to the injection speed of different drugs. And automatic control of liquid drip has been achieved through the fuzzy PID controller to control the output of stepper motor, which can reduce the risk of unattended infusion so as to guarantee the safety of all patients.
Office Online
Journal Online
Download
More>>
京ICP备05021913号-100
Copyright © Control Engineering of China, All Rights Reserved.
Tel: 024-23883498（传真），024-83688973-16/17/18　E-mail: kzgcbjb@mail.neu.edu.cn
Powered by Beijing Magtech Co., Ltd.