DocumentCode :
2133814
Title :
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
Link To Document :
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