DocumentCode :
2056715
Title :
Application of multiple fuzzy-neuro force controllers in an unknown environment using genetic algorithms
Author :
Kiguchi, Kazuo ; Watanabe, Keigo ; Izumi, Kiyotaka ; Fukuda, Toshio
Author_Institution :
Dept. of Mech. Eng., Saga Univ., Japan
Volume :
3
fYear :
2000
fDate :
2000
Firstpage :
2106
Abstract :
This paper presents an effective force control method in which multiple fuzzy-neuro force controllers are suitably and automatically combined with a proper rate in accordance with the unknown dynamics of an environment. The optimal combination rate of the fuzzy-neuro force controllers according to the environment dynamics is defined online by a neural network which is off-line trained with genetic algorithms. The effectiveness of the proposed method has been evaluated by computer simulation
Keywords :
adaptive control; force control; fuzzy control; fuzzy neural nets; genetic algorithms; neurocontrollers; robot dynamics; adaptive control; force control; fuzzy control; fuzzy neural network; genetic algorithms; neurocontrol; robot dynamics; Automatic control; Force control; Genetics; Humans; Jacobian matrices; Manipulator dynamics; Neural networks; Optimal control; Robot control; Robot kinematics;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Robotics and Automation, 2000. Proceedings. ICRA '00. IEEE International Conference on
Conference_Location :
San Francisco, CA
ISSN :
1050-4729
Print_ISBN :
0-7803-5886-4
Type :
conf
DOI :
10.1109/ROBOT.2000.846340
Filename :
846340
Link To Document :
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