Table of Content

20 August 2019, Volume 26 Issue 8

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Process Monitoring Method Based on Adaptive Threshold PLS and its Application

LIANG Meng-yuan, ZHOU Ping

2019, 26(8):  1437-1443. 

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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.

The Database Selection Based on Hesitant Linguistic Information Aggregation Algorithm

GAO Ting, WANG Xiao-nan

2019, 26(8):  1444-1449. 

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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.

Stability Analysis of Switched Positive Linear System

WANG Xiao-mei, MA Rui-cheng

2019, 26(8):  1450-1453. 

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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. 

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. 

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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.

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. 

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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.

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. 

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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.

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. 

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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.

Kalman Filter Complementary Fusion Method Based on Hammerstein System

WANG Jiang-hua, ZHANG Li, SUN Si-fan

2019, 26(8):  1479-1483. 

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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.

Research on H∞ Control of Uncertain Hamiltonian Systems

LAN Yong-hong, YIN Li-sha

2019, 26(8):  1484-1489. 

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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.

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. 

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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.

The Improved Particle Swarm Optimization Algorithm Based on PID Control Theory

YANG Xiao, WANG Guo-zhu

2019, 26(8):  1497-1502. 

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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.

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. 

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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.

An SLAM Method for Chaos Optimization Based on Chicken Swarm Algorithm

GE Yuan-yuan, ZHANG Hong-ji

2019, 26(8):  1509-1514. 

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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.

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. 

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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.

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

LUO Jin-sheng

2019, 26(8):  1521-1525. 

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 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.

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. 

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 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.

Research on Anomaly Detection Algorithm Based on Regular Change Background

YIN Rui, YANG Jian-hua, LU Wei

2019, 26(8):  1533-1538. 

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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.

Analysis of Track Irregularity Based on the Improved Hilbert-Huang Transform

ZHAO Ling, HUANG Da-rong, WANG Hong-gang

2019, 26(8):  1539-1543. 

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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.

Research on Power Plant Thermal Energy Combined Cycle Control Based on CNN Prediction

Ren Zhi-ling, Zhao Bo-ya

2019, 26(8):  1544-1549. 

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 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.

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. 

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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 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. 

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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.

Super-heated Steam Temperature Control System of Power Plant Based on Fuzzy Logic Controller and SPSO

SHUAI Hai-yan

2019, 26(8):  1561-1565. 

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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.

Three-link Robot Control System Design based on Parametric Solutions

GU Da-ke, TANG Chong-jian

2019, 26(8):  1566-1571. 

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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.

Active Disturbance Rejection Sliding Mode Controller Design for UAVs Close Formation

ZHAO Jing-xiang, TANG Bin

2019, 26(8):  1572-1577. 

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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.

Study on Grid-connected Control for Two Interconnected Generators

LIU Jian-hui, QUAN Xiao-chen

2019, 26(8):  1578-1584. 

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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.

Planning of Electric Vehicle Charging Station Based on Culture Algorithm

WANG Yv-hong, WANG Zhi-guo, QIU Wei

2019, 26(8):  1585-1591. 

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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.

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. 

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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.

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. 

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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.