DocumentCode
3198784
Title
The control of dynamical systems by neural networks
Author
Warwich, K.
Author_Institution
Dept. of Cybern., Reading Univ.
fYear
1995
fDate
5-7Jan 1995
Firstpage
341
Lastpage
346
Abstract
In this paper the use of neural networks for the control of dynamical systems is considered. Both identification and feedback control aspects are discussed as well as the types of system for which neural networks can provide a useful technique. Multilayer perceptron and radial basis function neural network types are looked at, with an emphasis on the latter. It is shown how basis function centre selection is a critical part of the implementation process and that multivariate clustering algorithms can be an extremely useful tool for finding centres
Keywords
feedback; feedforward neural nets; identification; multilayer perceptrons; neurocontrollers; pattern recognition; basis function centre selection; dynamical systems control; feedback control; identification; multilayer perceptron; multivariate clustering; neural networks; radial basis function neural network; Control systems; Cybernetics; Feedback control; Least squares approximation; Multilayer perceptrons; Neural networks; Nonlinear control systems; Parallel processing; Radial basis function networks; Robust stability;
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.1995.465817
Filename
465817
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