DocumentCode :
317946
Title :
A fast adaptive neural network system for intelligent control
Author :
Zaknich, Anthony ; Attikiouzel, Yianni
Author_Institution :
Dept. of Electr. & Electron. Eng., Western Australia Univ., Nedlands, WA, Australia
Volume :
2
fYear :
1997
fDate :
12-15 Oct 1997
Firstpage :
1023
Abstract :
An intelligent control system needs to adapt to new dynamics very quickly but also retain knowledge of past dynamics to be able to act effectively and quickly for repeat occurrences. One solution is to model the system with two neural networks in parallel whereby one network is trained a priori with a wide range of historical dynamics while the second one, is allowed to adapt itself to make up the differences between the first model and the real-time dynamics. Within this scheme, as the second network is called to adapt itself, the first one can be progressively trained to learn the new dynamics without adversely affecting the old training. A strategy of this type can be achieved very effectively the modified probabilistic neural network because it is constructed with local radial kernel functions and its adaptation mechanism is computationally simple and very fast. This is demonstrated using a complex nonlinear system whose characteristics suddenly change after initial training and then switch back to the original characteristics. Comparisons are made with other networks to show the important advantages of the modified probabilistic neural network
Keywords :
dynamics; intelligent control; large-scale systems; learning (artificial intelligence); neurocontrollers; nonlinear control systems; statistical analysis; adaptation mechanism; adaptive neural network system; complex nonlinear system; historical dynamics; intelligent control; local radial kernel functions; modified probabilistic neural network; real-time dynamics; Adaptive control; Adaptive systems; Dynamic range; Intelligent control; Kernel; Neural networks; Nonlinear dynamical systems; Programmable control; Real time systems; Switches;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
ISSN :
1062-922X
Print_ISBN :
0-7803-4053-1
Type :
conf
DOI :
10.1109/ICSMC.1997.638082
Filename :
638082
Link To Document :
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