DocumentCode
2213056
Title
State feedback NN control of non-affine nonlinear system with zero dynamics
Author
Ge, S.S. ; Zhang, J.
Author_Institution
Dept. of Electr. & Comput. Eng., Nat. Univ. of Singapore, Singapore
Volume
5
fYear
2003
fDate
4-6 June 2003
Firstpage
4530
Abstract
This paper focuses on adaptive control of non-affine nonlinear systems with zero dynamics using multiplayer neural networks (MNNs). Through neural network approximation, MNNs are used as the emulator of the implicit desired state feedback control. The closed-loop system is proved to be stable based on Lyapunov stability theory. It is shown that the tracking error converges to an adjustable neighborhood of the origin.
Keywords
Lyapunov methods; adaptive control; approximation theory; closed loop systems; neurocontrollers; state feedback; tracking; Lyapunov stability theory; adaptive control; closed-loop system; emulator; implicit desired state feedback control; multilayer neural networks; neural network approximation; neural network control; nonaffine nonlinear system; tracking error; zero dynamics; Adaptive control; Control systems; Linear systems; Multi-layer neural network; Neural networks; Neurofeedback; Nonlinear control systems; Nonlinear dynamical systems; Nonlinear systems; State feedback;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2003. Proceedings of the 2003
ISSN
0743-1619
Print_ISBN
0-7803-7896-2
Type
conf
DOI
10.1109/ACC.2003.1240555
Filename
1240555
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