Title :
Exponential convergence conditions for passive learning control
Author_Institution :
Coll. of Eng., California Univ., Riverside, CA, USA
Abstract :
This article analyzes the stability of both the system state and parameter estimates in passive learning control applications. The main focus of this study is persistence of excitation conditions for approximators with locally supported basis elements. This article derives the conditions, studies salient convergence related issues, and derives lower bounds on the convergence rate
Keywords :
adaptive control; convergence; learning systems; nonlinear control systems; parameter estimation; stability; state estimation; convergence rate lower bounds; excitation persistence conditions; exponential convergence conditions; locally supported basis elements; parameter estimates; passive learning control; stability; state estimates; Adaptive control; Control systems; Convergence; Educational institutions; Linear systems; Nonlinear control systems; Nonlinear dynamical systems; Parameter estimation; Stability analysis; State estimation;
Conference_Titel :
American Control Conference, 1997. Proceedings of the 1997
Conference_Location :
Albuquerque, NM
Print_ISBN :
0-7803-3832-4
DOI :
10.1109/ACC.1997.610897
