DocumentCode
1751611
Title
Neural network based adaptive tracking of uncertain nonlinear systems in triangular form
Author
Wang, Dan ; Huang, Jie
Author_Institution
Dept. of Autom. & Comput.-Aided Eng., Chinese Univ. of Hong Kong, Hong Kong
Volume
5
fYear
2001
fDate
2001
Firstpage
3545
Abstract
An adaptive neural network controller is developed for a class of uncertain nonlinear systems in triangular (pure-feedback) form. The design procedure is a combination of adaptive backstepping and neural network based design techniques. It is shown that, under appropriate assumptions, the solution of the closed-loop system is uniformly ultimately bounded, and the tracking error may be made arbitrarily small by adjusting the parameters in the control law
Keywords
adaptive control; closed loop systems; neurocontrollers; nonlinear control systems; adaptive backstepping; adaptive neural network controller; closed-loop system; control law; neural network based adaptive tracking; tracking error; triangular form; uncertain nonlinear systems; Adaptive control; Adaptive systems; Backstepping; Control systems; Intelligent networks; Neural networks; Nonlinear control systems; Nonlinear systems; Programmable control; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2001. Proceedings of the 2001
Conference_Location
Arlington, VA
ISSN
0743-1619
Print_ISBN
0-7803-6495-3
Type
conf
DOI
10.1109/ACC.2001.946183
Filename
946183
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