DocumentCode :
1102753
Title :
Neural network learning approach of intelligent multimodel controller
Author :
Al-Akhras, M.A. ; Aly, G.M. ; Green, R.J.
Author_Institution :
Dept. of Electr. Eng., King Saud Univ., Riyadh, Saudi Arabia
Volume :
143
Issue :
4
fYear :
1996
fDate :
7/1/1996 12:00:00 AM
Firstpage :
395
Lastpage :
400
Abstract :
The authors present a novel intelligent control scheme based on an artificial neural network. The proposed controller is based on the multimodel approach to improve the system performance of a complex control system of linear or nonlinear characteristics when it operates at various operating conditions. The multimodel control scheme depends on the multiple representation of a process using different models that generate the control signal needed to make the system follow a prescribed desired trajectory. The proposed controller is implemented by a multilayer neural network to locate the model that best represents the process and generate the desired control signal to drive the process along the desired path. The proposed controller is robust as it can accommodate high and sudden deviation from the prescribed trajectory. Simulation results are included to illustrate the potential of the controller developed
Keywords :
intelligent control; learning (artificial intelligence); multilayer perceptrons; neurocontrollers; complex control system; intelligent multimodel controller; multilayer neural network; neural network learning approach;
fLanguage :
English
Journal_Title :
Control Theory and Applications, IEE Proceedings -
Publisher :
iet
ISSN :
1350-2379
Type :
jour
DOI :
10.1049/ip-cta:19960391
Filename :
511265
Link To Document :
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