摘要
This paper presents an adaptive fuzzy control scheme based on modified genetic algorithm. In the control scheme, genetic algorithm is used to optimze the nonlinear quantization functions of the controller and some key parameters of the adaptive control algorithm. Simulation results show that this control scheme has satisfactory performance in MIMO systems, chaotic systems and delay systems.
This paper presents an adaptive fuzzy control scheme based on modified genetic algorithm. In the control scheme, genetic algorithm is used to optimze the nonlinear quantization functions of the controller and some key parameters of the adaptive control algorithm. Simulation results show that this control scheme has satisfactory performance in MIMO systems, chaotic systems and delay systems.
基金
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作者简介
Wang Pan was born in 1971. Now he is a lecturer and Ph. D. candidate in Huazhong University of Science andTechnology. His research interests include intelligent control, decision making and biomedical intelligentsystems.Xu Chengzhi was born in 1976. Now he is a M. S. candidate in Wuhan University of Technology. His research interests include intelligent control and applicatory computer software.Feng Shan was born in 1933. Now she is a Ph. D. advisor in Huazhong University of Science and Technology.Her research interests include intelligent integrated systems engineering, modeling and simulating of complex systems.Xu Aihua was born in 1979. Now she is a M. S. candidate in Wuhan University of Technology. Her research interests include intelligent control and applicatory computer software.
