Fuzzy control of nonlinear plants through rule-based cooperative particle swarm optimization

Author

Juang, Chia-Feng ; Lu, Chun-Feng ; Hsiao, Che-Meng ; Hsu, Chia-Hung

Author_Institution

Dept. of Electr. Eng., Nat. Chung-Hsing Univ., Taichung, Taiwan

fYear

2010

fDate

18-21 Aug. 2010

Firstpage

2094

Lastpage

2096

Abstract

This paper applies rule-based cooperative particle swarm optimization (RCPSO) to fuzzy controller design. Initially, there are no rules in the RCPSO-designed fuzzy rule-based system. An on-line clustering-based algorithm is used to generate new fuzzy rules automatically during fuzzy control process. For each newly generated fuzzy rule, the RCPSO optimizes all of its antecedent and consequent parameters using the idea of cooperative particle swarm optimization. Performance of the RCPSO is verified through a nonlinear plant control problem.

Keywords

control system synthesis; cooperative systems; fuzzy control; fuzzy set theory; fuzzy systems; knowledge based systems; nonlinear control systems; particle swarm optimisation; fuzzy controller design; fuzzy rule; nonlinear plant control; online clustering based algorithm; rule based cooperative particle swarm optimization; Algorithm design and analysis; Clustering algorithms; Fuzzy control; Mathematical model; Optimization; Particle swarm optimization; Training data; fuzzy control; fuzzy system optimization; particle swarm optimization; structure lerning;

fLanguage

English

Publisher

ieee

Conference_Titel

SICE Annual Conference 2010, Proceedings of

Conference_Location

Taipei

Print_ISBN

978-1-4244-7642-8

Type

conf

Filename

5602234