Evolutionary computing for optimizing type-2 fuzzy systems in intelligent control of non-linear dynamic plants

Author

Castillo, Oscar ; Huesca, Gabriel ; Valdez, Fevrier

Author_Institution

Dept. of Comput. Sci., Tijuana Inst. of Technol., Mexico

fYear

2005

fDate

26-28 June 2005

Firstpage

247

Lastpage

251

Abstract

We describe in this paper the use of evolutionary computing techniques for optimizing the design of intelligent controllers. Genetic algorithms can be used to optimize the topology of a fuzzy system for control. We are considering type-2 fuzzy logic for intelligent control and as a consequence the task of designing the fuzzy system is more difficult. We use hierarchical genetic algorithms because the problem of fuzzy system optimization requires a hierarchical chromosome for representing the information about membership functions and parameters.

Keywords

control system synthesis; fuzzy control; fuzzy logic; fuzzy systems; genetic algorithms; hierarchical systems; intelligent control; nonlinear dynamical systems; evolutionary computing; hierarchical chromosome; hierarchical genetic algorithm; intelligent control; intelligent controller design optimization; nonlinear dynamic plant; type-2 fuzzy logic; type-2 fuzzy system; Automatic control; Control systems; Fuzzy control; Fuzzy logic; Fuzzy sets; Fuzzy systems; Genetic algorithms; Intelligent control; Nonlinear dynamical systems; Topology;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Information Processing Society, 2005. NAFIPS 2005. Annual Meeting of the North American

Print_ISBN

0-7803-9187-X

Type

conf

DOI

10.1109/NAFIPS.2005.1548542

Filename

1548542