Towars a Theory of Stochastic Hybrid Systems
HSCC '00 Proceedings of the Third International Workshop on Hybrid Systems: Computation and Control
Reachability questions in piecewise deterministic Markov processes
HSCC'03 Proceedings of the 6th international conference on Hybrid systems: computation and control
A probabilistic approach to aircraft conflict detection
IEEE Transactions on Intelligent Transportation Systems
Control of systems integrating logic, dynamics, and constraints
Automatica (Journal of IFAC)
Medium term scheduling of a hydro-thermal system using stochastic model predictive control
Automatica (Journal of IFAC)
Robust, optimal predictive control of jump Markov linear systems using particles
HSCC'07 Proceedings of the 10th international conference on Hybrid systems: computation and control
Hi-index | 0.00 |
This paper focuses on hybrid systems whose discrete state transitions depend on both deterministic and stochastic events. For such systems, after introducing a suitable hybrid model called Discrete Hybrid Stochastic Automaton (DHSA), different finite-time optimal control approaches are examined: (1) Stochastic Hybrid Optimal Control (SHOC), that “optimistically” determines the trajectory providing the best trade off between the tracking performance and the probability that stochastic events realize as expected, under specified chance constraints; (2) Robust Hybrid Optimal Control (RHOC) that, in addition, less optimistically, ensures that the system remains within a specified safety region for all possible realizations of stochastic events. Sufficient conditions for the asymptotic convergence of the state vector are given for receding-horizon implementations of the above schemes. The proposed approaches are exemplified on a simple benchmark problem in production system management.