We consider in this paper a continuous time stochastic hybrid control system with finite time horizon. The objective is to minimize a nonlinear function of the state trajectory. The state evolves according to a nonlinear dynamics. The parameters of the dynamics of the system may change at discrete times lε, l = 0, 1, ..., according to a controlled Markov chain which has finite state and action spaces. Under the assumption that e is a small parameter, we justify an averaging procedure allowing us to establish that our problem can be approximated by the solution of some deterministic optimal control problem.
|Number of pages||16|
|Journal||SIAM Journal on Control and Optimization|
|Publication status||Published - Nov 1997|
- Asymptotic optimality
- Hybrid stochastic systems
- Markov decision processes
- Nonlinear dynamics