Control of a hybrid stochastic system

Eitan Altman*, Vladimir Gaitsgory

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)


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.

Original languageEnglish
Pages (from-to)307-314
Number of pages8
JournalSystems and Control Letters
Issue number4
Publication statusPublished - 1993
Externally publishedYes


  • asymptotic optimality
  • finite horizon
  • Hybrid stochastic systems
  • linear dynamics
  • Markov decision processes


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