DocumentCode :
2290497
Title :
Adaptive learning control of complex uncertain systems with nonlinear parameterization
Author :
Fang, Y. ; Xiao, X. ; Ma, B. ; Lu, G.
Author_Institution :
Inst. of Robotics & Autom. Inf. Syst., Nankai Univ.
fYear :
2006
fDate :
14-16 June 2006
Abstract :
In this paper, an adaptive learning control law is proposed to address complex uncertain systems with nonlinear parameterization. Specifically, the controller consists of: (i) a feedback type term, (ii) an adaptive mechanism for the unknown system parameters, and (iii) a learning-based technique to estimate the unknown periodic functions. As proven by a Lyapunov-based stability analysis, the designed adaptive learning control achieves global asymptotic tracking result for the system state while compensates for the uncertainty associated with the system parameters and the unknown periodic functions simultaneously
Keywords :
Lyapunov methods; adaptive control; control system synthesis; feedback; large-scale systems; learning systems; nonlinear control systems; uncertain systems; Lyapunov-based stability analysis; adaptive learning control; complex uncertain systems; feedback type term; nonlinear parameterization; periodic function estimation; Adaptive control; Automatic control; Control systems; Nonlinear control systems; Nonlinear dynamical systems; Programmable control; Robust stability; Time varying systems; Uncertain systems; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference, 2006
Conference_Location :
Minneapolis, MN
Print_ISBN :
1-4244-0209-3
Electronic_ISBN :
1-4244-0209-3
Type :
conf
DOI :
10.1109/ACC.2006.1657241
Filename :
1657241
Link To Document :
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