Control of a hybrid stochastic system |
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Authors: | Eitan Altman Vladimir Gaitsgory |
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Abstract: | We consider in this paper a continuous-time stochastic hybrid control system with a finite time horizon. The objective is to minimize a linear function of the expected state trajectory. The state evolves according to a linear dynamics. However, the parameters of the state evolution equation may change at discrete times according to a controlled Markov chain which has finite state and action spaces. We use a procedure similar in form to the maximum principle; this determines a control strategy which is asymptotically optimal as the number of transitions during the finite time horizon grows to infinity. |
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Keywords: | Hybrid stochastic systems asymptotic optimality linear dynamics Markov decision processes finite horizon |
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