Evolving fuzzy inference system by Tabu Search algorithm and its application to control

Author

Talbi, Nesrine ; Belarbi, Khaled

Author_Institution

Dept. of Electron., Jijel Univ., Jijel, Algeria

fYear

2011

fDate

7-9 April 2011

Firstpage

1

Lastpage

6

Abstract

Fuzzy controllers are represented by if-then rules and thus can provide a user friendly and understandable knowledge representation. Evolutionary algorithms have been widely used for optimal design of fuzzy logic controllers (FLCs). In this paper, we present an evolutionary algorithm based on Tabu Search (TS) for generating knowledge bases for fuzzy logic systems. The algorithm dynamically adjusts the membership functions and fuzzy rules according to different environments. it was tested on the control of angle of inverted pendulum.

Keywords

control system synthesis; evolutionary computation; fuzzy control; fuzzy reasoning; knowledge representation; nonlinear control systems; pendulums; search problems; evolutionary algorithm; fuzzy inference system; fuzzy logic controller; fuzzy logic system; fuzzy rule; if-then rule; inverted pendulum; knowledge base; knowledge representation; membership function; optimal design; tabu search algorithm; Algorithm design and analysis; Evolutionary computation; Fuzzy logic; Fuzzy systems; Knowledge based systems; Optimization; Search problems; control; evolutionary algorithm; fuzzy logic; inverted pendulum; tabu search;

fLanguage

English

Publisher

ieee

Conference_Titel

Multimedia Computing and Systems (ICMCS), 2011 International Conference on

Conference_Location

Ouarzazate

ISSN

Pending

Print_ISBN

978-1-61284-730-6

Type

conf

DOI

10.1109/ICMCS.2011.5945637

Filename

5945637