Title :
On developing an adaptive neural-fuzzy control system
Author :
Kim, Seong-Hyun ; Kim, Yong-Ho ; Sim, Kwee-Bo ; Jeon, Hong-Tae
Author_Institution :
Chung-Ang Univ., Seoul, South Korea
Abstract :
An adaptive neural-fuzzy control scheme for intelligent control is proposed. The control system consists of a fuzzy-neural controller (FNC) and model neural network (MNN). In the FNC, the antecedence and consequence of the fuzzy rule are constructed by a clustering method and a multilayer neural network. In the MNN, a multilayer neural network is utilized to identify an unknown controlled plant. The error backpropagation algorithm has been adopted as a learning technique. The effectiveness of the scheme is demonstrated by computer simulations of a cart-pole and a two-d.o.f. robot manipulator
Keywords :
adaptive control; adaptive neural-fuzzy control system; cart-pole system; clustering method; error backpropagation algorithm; fuzzy rule antecedence; fuzzy rule consequence; intelligent control; inverted pendulum; multilayer neural network; two-d.o.f. robot manipulator; Adaptive control; Adaptive systems; Clustering methods; Control system synthesis; Control systems; Fuzzy neural networks; Intelligent control; Multi-layer neural network; Neural networks; Programmable control;
Conference_Titel :
Intelligent Robots and Systems '93, IROS '93. Proceedings of the 1993 IEEE/RSJ International Conference on
Conference_Location :
Yokohama
Print_ISBN :
0-7803-0823-9
DOI :
10.1109/IROS.1993.583263
