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Proceedings Paper

A parameter-optimized analytic fuzzy controller based on a genetic algorithm
Author(s): Qing-kun Song; Jin-jie Huang; Zi-ying Hu; Mu-kun Wang
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Paper 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.

Paper Details

Date Published: 2 May 2006
PDF: 5 pages
Proc. SPIE 6042, ICMIT 2005: Control Systems and Robotics, 60421M (2 May 2006); doi: 10.1117/12.664621
Show Author Affiliations
Qing-kun Song, Harbin Univ. of Science and Technology (China)
Jin-jie Huang, Harbin Univ. of Science and Technology (China)
Zi-ying Hu, Harbin Univ. of Science and Technology (China)
Mu-kun Wang, Harbin Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 6042:
ICMIT 2005: Control Systems and Robotics
Yunlong Wei; Kil To Chong; Takayuki Takahashi; Shengping Liu; Zushu Li; Zhongwei Jiang; Jin Young Choi, Editor(s)

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