DocumentCode
354189
Title
Neural network adaptive control with fuzzy rules confirming initial weights
Author
Guiyong, Ren ; Yancheng, Qu ; Changhong, Wang
Author_Institution
Harbin Inst. of Technol., China
Volume
2
fYear
2000
fDate
2000
Firstpage
931
Abstract
A method, based on fuzzy rules, is presented to learn the initial values of a neural network´s weight array. This neural network is used in an adaptive control architecture. Using the prior knowledge efficiently, it can ensure the stability of the adaptive control during the learning period of the neural network. Simulation results demonstrate the feasibility of this method
Keywords
adaptive control; fuzzy control; learning (artificial intelligence); model reference adaptive control systems; neurocontrollers; stability; adaptive control architecture; fuzzy rules; initial values; learning period; neural network adaptive control; prior knowledge; weight array; Adaptive control; Fuzzy control; Fuzzy neural networks; Neural networks; Stability;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2000. Proceedings of the 3rd World Congress on
Conference_Location
Hefei
Print_ISBN
0-7803-5995-X
Type
conf
DOI
10.1109/WCICA.2000.863369
Filename
863369
Link To Document