DocumentCode :
630777
Title :
Adaptive control via embedding in reproducing kernel Hilbert spaces
Author :
Kurdila, Andrew ; Yu Lei
fYear :
2013
fDate :
17-19 June 2013
Firstpage :
3384
Lastpage :
3389
Abstract :
This paper derives a formulation of an adaptive tracking control problem for systems having uncertain nonlinear dynamics by embedding an original L1 adaptive control problem in a reproducing kernel Hilbert space (RKHS). This paper proves the well-posedness of the closed loop evolution laws in the RKHS and derives sufficient conditions for stability and tracking convergence. When the uncertainty in the dynamics is represented in a RKHS that satisfies certain fundamental smoothness properties, the adaptive controller yields a closed loop system whose stability and convergence properties are analogous to that obtained for conventional model reference and L1 control for systems of ordinary differential equations.
Keywords :
Hilbert spaces; adaptive control; closed loop systems; convergence; differential equations; nonlinear control systems; tracking; uncertain systems; L1 adaptive control problem; RKHS; adaptive tracking control problem; closed loop evolution laws; closed loop system; convergence properties; ordinary differential equations; reproducing kernel Hilbert space; stability convergence; tracking convergence; uncertain nonlinear dynamics; Adaptive control; Approximation methods; Convergence; Equations; Hilbert space; Kernel; Mathematical model;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
American Control Conference (ACC), 2013
Conference_Location :
Washington, DC
ISSN :
0743-1619
Print_ISBN :
978-1-4799-0177-7
Type :
conf
DOI :
10.1109/ACC.2013.6580354
Filename :
6580354
Link To Document :
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