A software development system for fuzzy control

被引：0

作者：

Yang, L ^{[1
]}

Guo, YK ^{[1
]}

Huang, X ^{[1
]}

机构：

[1] Shanghai Jiao Tong Univ, Inst Image Proc & Patern Recognit, Shanghai 200030, Peoples R China

来源：

ROBOTICA | 2000年 / 18卷

关键词：

fuzzy control; rule generation; multi-layer feedforward network; genetic algorithm;

D O I：

暂无

中图分类号：

TP24 [机器人技术];

学科分类号：

080202 ; 1405 ;

摘要：

Fuzzy control has been widely applied in industrial controls and domestic electrical equipment. The automatic learning of fuzzy rules is a key technique in fuzzy control. In this paper, a software development system for fuzzy control is presented. Since the learning of fuzzy rules can be seen as finding the best classifications of fuzzy memberships of input-output variables in a fuzzy controller, it can also be seen as the combination optimization of input-output fuzzy memberships. Multi-layer feedforward network and genetic algorithms (GA) can be used for the automatic learning of fuzzy rules. The algorithms and their characteristics are described. The software development system has been successfully used for the design of some fuzzy controllers.

引用

页码：375 / 380

页数：6

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