DocumentCode :
323334
Title :
An adaptive fuzzy control system for robotic manipulators
Author :
Dai, Min ; Lu, Wenjuan ; Sun, Fuchun
Author_Institution :
Dept. of Electr. Eng., Tsinghua Univ., Beijing, China
Volume :
1
fYear :
1997
fDate :
28-31 Oct 1997
Firstpage :
195
Abstract :
In this paper, an adaptive fuzzy control system is developed for robotic manipulators whose mathematical models are unknown. This control system is constructed by combining three methods, including an independent joint control strategy, to generate initial rules by using both data and linguistic information, and online parameter optimization through learning. The independent joint control strategy reduces the number of fuzzy rules, sample data and human experience provides information to construct initial rules which serve as initial values for parameter optimization. Parameter optimization is a key step exerting the approximation ability of adaptive fuzzy systems to compensate for the disturbances caused by the coupling effects and revising the incorrect components of the experiences used to construct initial rules. The backpropagation algorithm is applied due to the structural equivalence between adaptive fuzzy systems and multilayer feedforward neural networks. Initial rules help to improve the convergence ability of BP algorithm
Keywords :
adaptive control; backpropagation; convergence; feedforward neural nets; fuzzy control; manipulators; multilayer perceptrons; neurocontrollers; optimisation; adaptive fuzzy control; backpropagation; convergence; disturbance; fuzzy rules; independent joint control strategy; learning; linguistic information; mathematical models; multilayer feedforward neural networks; online parameter optimization; parameter optimization; robotic manipulators; Adaptive control; Adaptive systems; Backpropagation algorithms; Control systems; Fuzzy control; Fuzzy systems; Manipulators; Multi-layer neural network; Programmable control; Robots;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-4253-4
Type :
conf
DOI :
10.1109/ICIPS.1997.672764
Filename :
672764
Link To Document :
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