DocumentCode :
2310696
Title :
Training neural networks for robust control of nonlinear MIMO systems
Author :
Wams, B. ; Botto, M. Ayala ; van den Boom, T.J.J. ; Costa, J. Sá da
Author_Institution :
Dept. of Electr. Eng., Delft Univ. of Technol., Netherlands
Volume :
1
fYear :
1998
fDate :
1-4 Sep 1998
Firstpage :
241
Abstract :
A training strategy for computational neural networks is introduced that paves the way for incorporation of neural networks in robust control design for nonlinear multiple input, multiple output systems. The proposed training strategy enables utilization of statistical properties of the least-squares estimate. A control strategy that has a structural similarity to an adaptive control structure is adopted and it is outlined how neural networks which are trained with the proposed training strategy can be used to incorporate robustness in this control strategy
Keywords :
nonlinear control systems; adaptive control structure; computational neural networks; least-squares estimate; neural network training; nonlinear MIMO systems; robust control; statistical properties;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Control '98. UKACC International Conference on (Conf. Publ. No. 455)
Conference_Location :
Swansea
ISSN :
0537-9989
Print_ISBN :
0-85296-708-X
Type :
conf
DOI :
10.1049/cp:19980234
Filename :
727915
Link To Document :
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