DocumentCode :
2970644
Title :
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
Link To Document :
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