DocumentCode :
3208113
Title :
Multi-model neural network-based intelligent controller
Author :
Al-Akhras, Mohammad A. ; Aly, Gamal M. ; Green, Roger J.
Author_Institution :
Dept. of Electr. Eng., King Saud Univ., Riyadh, Saudi Arabia
fYear :
1995
fDate :
5-7Jan 1995
Firstpage :
49
Lastpage :
53
Abstract :
A new multi-model intelligent control scheme based on an artificial neural network is presented in this paper. The proposed controller is used to improve the system performance of a complex control system of known or unknown model by driving the process to follow the desired trajectory. The multi-model control scheme depends on the multiple representation of a process using different models, involving two phases; (i) locating the model that best matches the process, and (ii) generating the basic control signal that will drive the system to follow the desired trajectory according to the located model. A multilayer neural network is used to implement both phases of the multi model scheme. The proposed controller can accommodate any deviation from the prescribed models. Simulation results are presented to show the potential of developed scheme
Keywords :
intelligent control; neurocontrollers; complex control system; multi-model neural network-based intelligent controller; multilayer neural network; Artificial intelligence; Artificial neural networks; Control system synthesis; Intelligent control; Intelligent networks; Multi-layer neural network; Neural networks; Signal generators; Signal processing; System performance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Automation and Control, 1995 (I A & C'95), IEEE/IAS International Conference on (Cat. No.95TH8005)
Conference_Location :
Hyderabad
Print_ISBN :
0-7803-2081-6
Type :
conf
DOI :
10.1109/IACC.1995.465869
Filename :
465869
Link To Document :
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