Wang Debiao

Chongqing University of Science & Technology, Ch’ung-ch’ing-shih, Chongqing Shi, China

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Publications (3)0 Total impact

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    ABSTRACT: In order to most effectively utilize the wind energy and improve the efficiency of wind generation system, an optimum control strategy of doublyfed induction generators (DFIG) was proposed, which made the system operation for both the maximum wind enemy captured below the rated wind speed. Based on the wind turbine characteristics and basic electromagnetic relationship of DFIG the mathematical models of the stator active power and reactive power of DFIG were derived to fulfill maximal wind energy capture and conversion. A dual-passage excitation fuzzy control strategy based on dynamic synchronous reference frame was applied to control the proposed optimal stator active and reactive power. The operational performances of the wind turbine system with DFIG with wind speed variation were analyzed and compared by using Matlab/Simulink . The results show the correctness and feasibility of the proposed control strategy.
    Cognitive Informatics (ICCI), 2010 9th IEEE International Conference on; 08/2010
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    ABSTRACT: PID controller can not perform well in liquid level control system because liquid system has characteristics of time-delay and inertia. Based on the characteristics of two-tank liquid control system, an ADRC is designed by using control technique of active disturbance rejection. In order to study the control performance of ADRC, the comparative analysis with PID controller is to be carried out in the research. Simulation research shows that water level control system based on ADRC possesses better rapidity, less overshoot and strong disturbance inhibition compared with PID controller. Thus, the research result is of important guidance for engineering of water level control.
  • Wang Debiao, Li Taifu, Zhong Bingxiang
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    ABSTRACT: The combination of widely-used PID controller with fuzzy system generates fuzzy PID controller which possesses excellent control quality. However, the fuzzy PID controller has some problems of computation complexity and real-time performance. To solve these problems, the paper expounds the process of training BP neural network through its universal function approximating ability and PID controllerpsilas input and output couple. Simulation researches reveal that the fuzzy PID controller can be effectively replaced by the trained BP neural network. Therefore, the method can simplify the computation complexity, enhance the real-time performance of fuzzy PID controller, and promote its implementation by hardware.
    01/2008; 21(4). DOI:10.1109/WCICA.2008.4594435