Parameters integrated optimization of fuzzy controller based on improved genetic algorithm

被引：0

作者：

Dong Haiying ^{[1
]}

Xing Dongfeng ^{[1
]}

机构：

[1] Lanzhou Jiaotong Univ, Sch Automat & Elect Engn, Lanzhou 730070, Peoples R China

来源：

ISTM/2007: 7TH INTERNATIONAL SYMPOSIUM ON TEST AND MEASUREMENT, VOLS 1-7, CONFERENCE PROCEEDINGS | 2007年

关键词：

genetic algorithm (GA); nonlinear simplex method; fuzzy control; Parameter optimization;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In order to improve the control performance of fuzzy control system the genetic algorithm(GA) is used to optimize the parameters of fuzzy controller In this optimization approach, GA is combined with nonlinear simplex method. Using nonlinear simplex method to initialize the GA, and from the result nonlinear simplex method can search better individual. It can also avoid local extremum produced by using single nonlinear simplex method solely. Simulation proves it is a more effective method than traditional GA.

引用

页码：2676 / 2679

页数：4

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