Hierarchical genetic algorithms for topology optimization in fuzzy control systems

被引：21
|
作者：
Castillo, Oscar [1 ]
Valdez, Fevrier [1 ]
Melin, Patricia [1 ]
机构：
[1] Tijuana Inst Technol, Div Grad Studies & Res, Chula Vista, CA 91909 USA
来源：
INTERNATIONAL JOURNAL OF GENERAL SYSTEMS | 2007年 / 36卷 / 05期
关键词：
fuzzy control system; hierarchical genetic algorithms; membership functions; neural network;
D O I：
10.1080/03081070701321860
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
We describe in this paper the use of hierarchical genetic algorithms (HGA) for fuzzy system optimization in intelligent control. In particular, we consider the problem of optimizing the number of rules and membership functions using an evolutionary approach. The HGA enables the optimization of the fuzzy system design for a particular application. We illustrate the approach with two cases of intelligent control. Simulation results for both applications show that we are able to find an optimal set of rules and membership functions for the fuzzy control system.
引用
收藏
页码：575 / 591
页数：17
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