DocumentCode
2339615
Title
Decoupling of a class of nonlinear discrete time systems using neural networks
Author
Wu, Liming ; Chai, Tianyou
Author_Institution
Res. Center for Autom. & Control, Northeastern Univ., Shenyang, China
Volume
6
fYear
1995
fDate
21-23 Jun 1995
Firstpage
4275
Abstract
In this paper, the decoupling problem for a class of nonlinear discrete time systems is considered. A necessary and sufficient condition for the solvability of the decoupling problem for a class of discrete time systems is given. It is also shown that if the decoupling problem is solvable, the modified systems can be linear. Based on the result, a strategy for realizing decoupling using neural networks is proposed. Simulation in this paper supports the authors´ theory and the decoupling strategy
Keywords
discrete time systems; neural nets; nonlinear control systems; decoupling problem; necessary and sufficient condition; neural networks; nonlinear discrete time systems; Artificial neural networks; Automatic control; Automation; Continuous time systems; Control systems; Control theory; Discrete time systems; Neural networks; Nonlinear control systems; Sufficient conditions;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, Proceedings of the 1995
Conference_Location
Seattle, WA
Print_ISBN
0-7803-2445-5
Type
conf
DOI
10.1109/ACC.1995.532741
Filename
532741
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