Optimization of fuzzy controller based on genetic algorithm

Dongqing Feng; Jianzhong Jia; Tiejun Chen; Minrui Fei

doi:10.1117/12.718139

30 October 2006 Optimization of fuzzy controller based on genetic algorithm

Dongqing Feng, Jianzhong Jia, Tiejun Chen, Minrui Fei

Proceedings Volume 6358, Sixth International Symposium on Instrumentation and Control Technology: Sensors, Automatic Measurement, Control, and Computer Simulation; 63583M (2006) https://doi.org/10.1117/12.718139
Event: Sixth International Symposium on Instrumentation and Control Technology, 2006, Beijing, China

Abstract

It is pivotal to choose the parameters of control rules, membership function in designing a fuzzy controller. Genetic Algorithm is an effective method to optimize it. Based on hardly to find the best solution when the number of parameters to be optimized is too large, a step-by-step method to optimize the parameters of fuzzy controller is proposed. After discussion, only a quarter of control rules need to be optimized. To eliminate the system error, an integrator is connected with the fuzzy controller in parallel. Simulation results show that proposed design scheme can acquire the satisfied dynamic performance by learning and genetic optimization even for lack of any prior knowledge.

Citation Download Citation

Dongqing Feng, Jianzhong Jia, Tiejun Chen, and Minrui Fei "Optimization of fuzzy controller based on genetic algorithm", Proc. SPIE 6358, Sixth International Symposium on Instrumentation and Control Technology: Sensors, Automatic Measurement, Control, and Computer Simulation, 63583M (30 October 2006); https://doi.org/10.1117/12.718139

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