Abstract
In this paper, we study the problem of controlling the expected exit time from a region for a class of stochastic hybrid systems. That is, we find the least costly feedback control for a stochastic hybrid system that can keep its state inside a prescribed region for at least an expected amount of time. The stochastic hybrid systems considered are quite general: the continuous dynamics are governed by stochastic differential equations, and the discrete mode evolves according to a continuous time Markov chain. Instead of adopting the usual Hamilton-Jacobi viewpoint, we study the problem directly by formulating it as a PDE constrained optimization problem, and propose a solution using adjoint-based gradient descent methods. Numerical results of the proposed approach are presented for several representative examples, and, for the simple case, compared with analytical results.
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Raffard, R.L., Hu, J., Tomlin, C.J. (2005). Adjoint-Based Optimal Control of the Expected Exit Time for Stochastic Hybrid Systems. In: Morari, M., Thiele, L. (eds) Hybrid Systems: Computation and Control. HSCC 2005. Lecture Notes in Computer Science, vol 3414. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31954-2_36
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DOI: https://doi.org/10.1007/978-3-540-31954-2_36
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