On Asymptotic Optimization of a Class of Nonlinear Stochastic Hybrid Systems

Peng Shi, Eitan Altman, Vladimir Gaitsgory

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)

Abstract

We consider the problem of control for continuous time stochastic hybrid systems in finite time horizon. The systems considered are nonlinear: the state evolution is a nonlinear function of both the control and the state. The control parameters change at discrete times according to an underlying controlled Markov chain which has finite state and action spaces. The objective is to design a controller which would minimize an expected nonlinear cost of the state trajectory. We show using an averaging procedure, that the above minimization problem can be approximated by the solution of some deterministic optimal control problem. This paper generalizes our previous results obtained for systems whose state evolution is linear in the control.

Original languageEnglish
Pages (from-to)289-315
Number of pages27
JournalMathematical Methods of Operations Research
Volume47
Issue number2
Publication statusPublished - 1998
Externally publishedYes

Keywords

  • Hybrid stochastic systems
  • Markov decision processes
  • Nonlinear systems

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