Discrete Time Stochastic Adaptive Control

https://doi.org/10.1137/0319052

Abstract

This paper establishes global convergence of a stochastic adaptive control algorithm for discrete time linear systems. It is shown that, with probability one, the algorithm will ensure the system inputs and outputs are sample mean square bounded and the conditional mean square output tracking error achieves its global minimum possible value for linear feedback control. Thus, asymptotically, the adaptive control algorithm achieves the same performance as could be achieved if the system parameters were known.

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Volume 19, Issue 6| 1981

SIAM Journal on Control and Optimization

History

Submitted:08 January 1979
Accepted:01 November 1980
Published online:17 February 2012

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Article DOI:10.1137/0319052

Article page range:pp. 829-853

ISSN (print):0363-0129

ISSN (online):1095-7138

Publisher:Society for Industrial and Applied Mathematics

Discrete Time Stochastic Adaptive Control

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