On residence probability control

Author

Kim, S. ; Meerkov, S.M. ; Runolfsson, T.

Author_Institution

Dept. of Electr. Eng. & Comput. Sci., Michigan Univ., Ann Arbor, MI, USA

fYear

1988

fDate

7-9 Dec 1988

Firstpage

276

Abstract

The problem of controlling the residence probability of a linear stochastic system in a bounded domain is considered. Necessary and sufficient conditions for the existence of a controller that makes the residence probability positive (weakly residence-probability-controllable systems) and arbitrarily close to one (strongly residence-probability-controllable systems) are derived. The approach is based on the modern large-deviations theory for systems perturbed by small white noise. It is concluded that system is weakly residence-probability-controllable if and only if it is stabilizable (in a certain sense) on the interval [0, T], and it is strongly residence-probability-controllable if and only if the image of the noise input matrix is contained in the image of the control input matrix

Keywords

control system analysis; linear systems; probability; stochastic systems; control input matrix; linear stochastic system; necessary conditions; noise input matrix; perturbation; residence probability control; sufficient conditions; white noise; Contracts; Control systems; Linear feedback control systems; Linear systems; Modems; Motion control; State feedback; Stochastic systems; Sufficient conditions; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Decision and Control, 1988., Proceedings of the 27th IEEE Conference on

Conference_Location

Austin, TX

Type

conf

DOI

10.1109/CDC.1988.194309

Filename

194309