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