DocumentCode :
3526556
Title :
Discrete-time adaptive learning control for parametric uncertainties with unknown periods
Author :
Miao Yu ; Deqing Huang
Author_Institution :
Dept. of Biotechnol. & Chem. Technol., Aalto Univ., Aalto, Finland
fYear :
2013
fDate :
10-13 Dec. 2013
Firstpage :
1786
Lastpage :
1791
Abstract :
In this paper, we approach the problem of unknown periods for a class of discrete-time parametric nonlinear systems with nonlinearities which do not necessarily satisfy the sector-bounded condition. The unknown periods hide in the parametric uncertainties, which is difficult to estimate. By incorporating a logic-based switching mechanism, we estimate the period and bound of unknown parameter simultaneously under Lyapunov-based analysis. Rigorous proof is given to demonstrate that a finite number of switchings can guarantee the asymptotic regulation of the nonlinear system considered. The simulation result also shows the efficacy of the proposed switching periodic adaptive control method.
Keywords :
Lyapunov methods; adaptive control; control nonlinearities; discrete time systems; iterative methods; learning systems; nonlinear control systems; parameter estimation; periodic control; time-varying systems; uncertain systems; Lyapunov-based analysis; asymptotic nonlinear system regulation; discrete-time adaptive learning control; discrete-time parametric nonlinear systems; logic-based switching mechanism; nonlinearities; parametric uncertainties; switching periodic adaptive control method; unknown parameter bound estimation; unknown parameter period estimation; unknown periods; Nickel; Switches;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control (CDC), 2013 IEEE 52nd Annual Conference on
Conference_Location :
Firenze
ISSN :
0743-1546
Print_ISBN :
978-1-4673-5714-2
Type :
conf
DOI :
10.1109/CDC.2013.6760141
Filename :
6760141
Link To Document :
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