Optimal Design of T-S Fuzzy Controller Based on Improved Genetic Algorithm

被引：0
|
作者：
Dong Ling-jiao [1 ]
Su Shao-xing [1 ]
机构：
[1] Wenzhou Vocat & Tech Coll, Dept Elect & Elect, Wenzhou 325035, Zhejiang, Peoples R China
来源：
COMPUTATIONAL MATERIALS SCIENCE, PTS 1-3 | 2011年 / 268-270卷
关键词：
Takagi-Sugno; fuzzy controller; genetic algorithm; optimal; time-varying parameters;
D O I：
10.4028/www.scientific.net/AMR.268-270.924
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
To solving the problem that there had been too many undetermined parameters in the fuzzy control rules, it presented a simplified Takagi-Sugno, namely T-S, fuzzy reasoning method. It reduced the parameters of the IF-THEN rules greatly. In addition this paper also improved the genetic algorithm on the analysis of the prior genetic algorithm, by which the global optimal parameters of the controller can be found easily and quickly thus the control rules can be amended and perfected. The simulation results show that the improved genetic algorithm can find the optimal parameters at a high speed and the optimized T-S fuzzy controller can obtain an excellent control performance.
引用
收藏
页码：924 / 929
页数：6
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