Towars a Theory of Stochastic Hybrid Systems
HSCC '00 Proceedings of the Third International Workshop on Hybrid Systems: Computation and Control
Measurability and safety verification for stochastic hybrid systems
Proceedings of the 14th international conference on Hybrid systems: computation and control
Safety verification for probabilistic hybrid systems
CAV'10 Proceedings of the 22nd international conference on Computer Aided Verification
Rewarding probabilistic hybrid automata
Proceedings of the 16th international conference on Hybrid systems: computation and control
A compositional modelling and analysis framework for stochastic hybrid systems
Formal Methods in System Design
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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 $l\epsilon$, $l=0,1,...$, according to a controlled Markov chain which has finite state and action spaces. Under the assumption that $\epsilon$ 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.