Optimal and stable fuzzy controllers for nonlinear systems based on an improved genetic algorithm

被引：36
|
作者：
Leung, FHF [1 ]
Lam, HK [1 ]
Ling, SH [1 ]
Tam, PKS [1 ]
机构：
[1] Hong Kong Polytech Univ, Ctr Multimedia Signal Proc, Dept Elect & Informat Engn, Kowloon, Hong Kong, Peoples R China
来源：
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS | 2004年 / 51卷 / 01期
关键词：
fuzzy control; nonlinear systems; optimality and stability;
D O I：
10.1109/TIE.2003.821898
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper addresses the optimization and stabilization problems of nonlinear systems subject to parameter uncertainties. The methodology is based on a fuzzy logic approach and an improved genetic algorithm (GA). The TSK fuzzy plant model is employed to describe the dynamics of the uncertain nonlinear plant. A fuzzy controller is then obtained to close the feedback loop. The stability conditions are derived. The feedback gains of the fuzzy controller and the solution for meeting the stability conditions are determined using the improved GA. In order to obtain the optimal fuzzy controller, the membership functions are further tuned by minimizing a defined fitness function using the improved GA. An application example on stabilizing a two-link robot. arm will be given.
引用
收藏
页码：172 / 182
页数：11
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