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Proceedings Paper

Optimization of fuzzy controller based on genetic algorithm
Author(s): Dongqing Feng; Jianzhong Jia; Tiejun Chen; Minrui Fei
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Paper 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.

Paper Details

Date Published: 30 October 2006
PDF: 5 pages
Proc. SPIE 6358, Sixth International Symposium on Instrumentation and Control Technology: Sensors, Automatic Measurement, Control, and Computer Simulation, 63583M (30 October 2006); doi: 10.1117/12.718139
Show Author Affiliations
Dongqing Feng, Zhengzhou Univ. (China)
Shanghai Univ. (China)
Jianzhong Jia, Zhengzhou Univ. (China)
Tiejun Chen, Zhengzhou Univ. (China)
Minrui Fei, Shanghai Univ. (China)


Published in SPIE Proceedings Vol. 6358:
Sixth International Symposium on Instrumentation and Control Technology: Sensors, Automatic Measurement, Control, and Computer Simulation
Jiancheng Fang; Zhongyu Wang, Editor(s)

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