DocumentCode :
2045904
Title :
Generation of adjustment strategy of fuzzy-neural force controllers using genetic algorithms with fuzzy evaluation
Author :
Kiguchi, Kazuo ; Watanabe, Keigo ; Izumi, Kiyotaka ; Fukuda, Toshio
Author_Institution :
Dept. of Adv. Control Syst. Eng., Saga Univ., Japan
Volume :
1
fYear :
2000
fDate :
2000
Firstpage :
620
Abstract :
This paper presents an effective force control method in which a fuzzy-neuro force controller is automatically adjusted in accordance with the unknown dynamics of an environment using a neural network. The adjustment strategy of the fuzzy-neural force controller, according to the environment dynamics, is automatically generated by the neural network in off-line manner using genetic algorithms with fuzzy evaluation. The effectiveness of the proposed force controller is evaluated by computer simulation with a 3-DOF planar robot manipulator model
Keywords :
force control; fuzzy control; genetic algorithms; manipulator dynamics; neurocontrollers; adjustment strategy; dynamics; force control; fuzzy control; genetic algorithms; input adjustment neural network; neurocontrol; robot manipulator; Automatic control; Automatic generation control; Computer simulation; Force control; Fuzzy control; Fuzzy neural networks; Genetic algorithms; Manipulators; Neural networks; Robotics and automation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics Society, 2000. IECON 2000. 26th Annual Confjerence of the IEEE
Conference_Location :
Nagoya
Print_ISBN :
0-7803-6456-2
Type :
conf
DOI :
10.1109/IECON.2000.973221
Filename :
973221
Link To Document :
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