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.