Abstract
The problem of controlling the residence probability of linear stochastic systems 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.
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