DocumentCode :
1395914
Title :
Adaptive control and identification using one neural network for a class of plants with uncertainties
Author :
Tsuji, Toshio ; Xu, Bing Hong ; Kaneko, Makoto
Author_Institution :
Dept. of Ind. & Syst. Eng., Hiroshima Univ., Japan
Volume :
28
Issue :
4
fYear :
1998
fDate :
7/1/1998 12:00:00 AM
Firstpage :
496
Lastpage :
505
Abstract :
This paper proposes a new neural adaptive control method that can perform adaptive control and identification for a class of controlled plants with linear and nonlinear uncertainties. This method uses a single neural network for both control and identification, and a sufficient condition of the local asymptotic stability is derived. Then, in order to illustrate the applicability of the proposed method, it is applied to the torque control of a flexible beam that includes linear and nonlinear structural uncertainties
Keywords :
adaptive control; asymptotic stability; backpropagation; flexible structures; identification; multilayer perceptrons; neurocontrollers; torque control; uncertain systems; adaptive control; asymptotic stability; backpropagation; flexible beam; identification; multilayer perceptron; neural network; neurocontrol; sufficient condition; torque control; uncertain systems; Adaptive control; Control systems; Error correction; Multi-layer neural network; Neural networks; Neurofeedback; Programmable control; Stability; Sufficient conditions; Uncertainty;
fLanguage :
English
Journal_Title :
Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on
Publisher :
ieee
ISSN :
1083-4427
Type :
jour
DOI :
10.1109/3468.686711
Filename :
686711
Link To Document :
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