A genetic-algorithm-and-table-rotating-based method for optimizing fuzzy control rules

Author

Manhuai, Zhang ; Yongquan, Yu ; Bi, Zeng

Author_Institution

Dept. of Comput. Sci. & Eng., Guangdong Univ. of Technol., Guangzhou, China

Volume

3

fYear

2000

fDate

2000

Firstpage

1803

Abstract

It has been demonstrated many times in practice that fuzzy logic controllers have an important role in rule-based expert systems. However, it is essential for a fuzzy logic controller to have an appropriate set of rules to perform at the desired level. The linguistic structure of the fuzzy logic controller allows a tentative linguistic policy to be used as an initial rule base. At the design stage, if one can assemble a reasonably good collection of rules, it may then be possible to tune these rules to improve the controller performance. In the paper, a genetic-algorithm-and-table-rotating-based method for optimizing fuzzy control rules and the simulation result are presented. Finally, the results are discussed

Keywords

fuzzy control; genetic algorithms; intelligent control; fuzzy control rules; fuzzy logic controllers; genetic-algorithm-and-table-rotating-based method; initial rule base; linguistic structure; rule-based expert systems; Assembly; Bismuth; Control systems; Expert systems; Fuzzy control; Fuzzy logic; Genetic algorithms; Optimization methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on

Conference_Location

Hefei

Print_ISBN

0-7803-5995-X

Type

conf

DOI

10.1109/WCICA.2000.862785

Filename

862785