A parameter-optimized analytic fuzzy controller based on a genetic algorithm

Qing-kun Song; Jin-jie Huang; Zi-ying Hu; Mu-kun Wang

doi:10.1117/12.664621

2 May 2006 A parameter-optimized analytic fuzzy controller based on a genetic algorithm

Qing-kun Song, Jin-jie Huang, Zi-ying Hu, Mu-kun Wang

Proceedings Volume 6042, ICMIT 2005: Control Systems and Robotics; 60421M (2006) https://doi.org/10.1117/12.664621
Event: ICMIT 2005: Merchatronics, MEMS, and Smart Materials, 2005, Chongqing, China

Abstract

A fuzzy controller based on analytic rules, which can self-adjust the fuzzy rules online, has good performance. That can change the output of the controller by modifying the fuzzy rules. An improved structure of a fuzzy controller based on analytic rules was proposed, and a modifying function aiming to regulate the fuzzy rules dynamically was introduced. The novel approach can effectively alleviate the contradictions between speediness and overshoot. Moreover, the genetic algorithm was applied to optimize five parameters of the fuzzy controller simultaneously. The steps required in seeking optimized parameters are presented. Simulation was conducted to show the efficiency of the proposed approach.

Citation Download Citation

Qing-kun Song, Jin-jie Huang, Zi-ying Hu, and Mu-kun Wang "A parameter-optimized analytic fuzzy controller based on a genetic algorithm", Proc. SPIE 6042, ICMIT 2005: Control Systems and Robotics, 60421M (2 May 2006); https://doi.org/10.1117/12.664621

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