Design of fuzzy control system by a new DNA-based immune genetic algorithm

Author

Ren, Lihong ; Ding, Yongsheng

Author_Institution

Dept. of Commun. & Electron. Inf. Eng., Dong Hua Univ., Shanghai, China

Volume

1

fYear

2001

fDate

6/23/1905 12:00:00 AM

Firstpage

244

Lastpage

247

Abstract

A new DNA-based immune genetic algorithm (DNA-IGA) is proposed to design a class of Takagi-Sugeno fuzzy control systems. The DNA-IGA is developed from the structures of biological immune system and DNA. The genetic operators of the method are based on the DNA genetic operations and evaluation of immune system. It uses DNA encoding method stemmed from the biological DNA to encode the design parameters of the fuzzy controllers. The DNA encoding method can significantly shorten the code length of antibodies and is suitable for complex knowledge representation. The proposed method has the local search ability and prevents the premature convergence. As a demonstration, we show how to implement the new method to optimize the design parameters of the TS fuzzy controller in control of a nonlinear system. Computer simulation indicates that the designed fuzzy controller is satisfactory

Keywords

control system synthesis; fuzzy control; genetic algorithms; intelligent control; knowledge representation; optimal control; DNA-IGA; DNA-based immune genetic algorithm; GA; TS fuzzy controller; antibody code length shortening; complex knowledge representation; design parameter optimization; fuzzy control system design; local search ability; nonlinear system control; premature convergence; Algorithm design and analysis; Biological information theory; Control systems; DNA; Encoding; Fuzzy control; Genetic algorithms; Immune system; Nonlinear control systems; Takagi-Sugeno model;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2001. The 10th IEEE International Conference on

Conference_Location

Melbourne, Vic.

Print_ISBN

0-7803-7293-X

Type

conf

DOI

10.1109/FUZZ.2001.1007294

Filename

1007294