DocumentCode :
2129443
Title :
Towards a stability and approximation theory for neuro-controllers
Author :
Mason, J.D. ; Craddock, R.J. ; Mason, J.C. ; Parks, P.C. ; Warwick, K.
Author_Institution :
Reading Univ., UK
Volume :
1
fYear :
1994
fDate :
21-24 March 1994
Firstpage :
100
Abstract :
This paper discusses issues related to the control of systems using neural networks. The importance of convergence speed in adaptive systems is observed leading to the use of approximation functions such as the radial basis function (RBF) rather than back propagation. Initial trials have been conducted using RBFs for system identification and the results are reported. Attention has been given to the choice of number and location of RBF centres, both of factors having significant influence on the network performance. The aim of the research is to establish stability for certain classes of neuro-controller and initial thoughts are recorded here.
Keywords :
adaptive control; approximation theory; feedforward neural nets; stability; adaptive systems; approximation theory; convergence speed; neural networks; neuro-controllers; radial basis function; stability;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Control, 1994. Control '94. International Conference on
Conference_Location :
Coventry, UK
Print_ISBN :
0-85296-610-5
Type :
conf
DOI :
10.1049/cp:19940117
Filename :
327160
Link To Document :
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