Title:

A new approach to convergence analysis of RLS-based self-tuning stochastic control

Group publication title:

AMCS, volume 7 (1997)

Creator:

Niederliński, Antoni

Subject and Keywords:

sterowanie ; sztuczna inteligencja ; informatyka ; sterowanie-teoria ; matematyka stosowana

Abstract:

It is demonstrated that a recently derived bound on the error convergence rate in (open-loop) RLS estimation is applicable to RLS-based stochastic self-tuning control as well. This leads to a generalized upper bound for the estimation error convergence rate in stochastic self-tuning control. The bound is shown to converge to zero under some assumptions regarding the model structure. The result is used to formulate two principles of self-tuning stating sufficient conditions under which self-tuning to stability and self-tuning to parameter consistency may occur.

Publisher:

Zielona Góra: Uniwersytet Zielonogórski

Contributor:

Korbicz, Józef - red. ; Uciński, Dariusz - red.

Date:

1997

Resource Type:

artykuł

Pages:

27-40

Source:

AMCS, volume 7, number 1 (1997)

Language:

eng

Rights:

Biblioteka Uniwersytetu Zielonogórskiego