DocumentCode :
2947431
Title :
Adaptive fuzzy logic controller of visual servoing robot system by membership optimization using genetic algorithms
Author :
Fares, Essam A. ; Elbardiny, Mohamed ; Sharaf, Mohamed M.
Author_Institution :
Menufia Univ., Shibin El Kom
fYear :
2007
fDate :
27-29 Nov. 2007
Firstpage :
15
Lastpage :
20
Abstract :
In this paper, fuzzy logic control systems (FLC) and genetic algorithm (GA) are integrated for adaptive fuzzy logic controller to control visual servoing robot. Genetic algorithms are employed as an adaptive method for optimizing the internal parameters of fuzzy membership functions. The overall optimization of membership functions is done by selection of randomly generated parameters. Fitness function plays a crucial role in parameters selection .A proposed visual servoing simulator is used to verify the effectiveness of the proposed manner to control position-based visual servoing robot manipulator.
Keywords :
adaptive control; fuzzy control; genetic algorithms; manipulators; robot vision; visual servoing; adaptive fuzzy logic controller; fitness function; fuzzy membership function optimization; genetic algorithm; parameter selection; visual servoing robot manipulator; Adaptive control; Automatic control; Control systems; Fuzzy control; Fuzzy logic; Genetic algorithms; Programmable control; Robot vision systems; Robotic assembly; Visual servoing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer Engineering & Systems, 2007. ICCES '07. International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-1365-2
Electronic_ISBN :
978-1-1244-1366-9
Type :
conf
DOI :
10.1109/ICCES.2007.4447019
Filename :
4447019
Link To Document :
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