Abstract
In this paper, an optimal control problem over a "hybrid Markov Chain" (hMC) is studied. A hMC can be thought of as a traditional MC with continuous time dynamics pertaining to each node; from a different perspective, it can be regarded as a class of hybrid system with random discrete switches induced by an embedded MC. As a consequence of this setting, the index to be maximized, which depends on the dynamics, is the expected value of a non deterministic cost function. After obtaining a closed form for the objective function, we gradually suggest how to device a computationally tractable algorithm to get to the optimal value. Furthermore, the complexity and rate of convergence of the algorithm is analyzed. Proofs and simulations of our results are provided; moreover, an applicative and motivating example is introduced.
| Original language | English |
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| Article number | WeB01.1 |
| Pages (from-to) | 1842-1847 |
| Number of pages | 6 |
| Journal | Proceedings of the IEEE Conference on Decision and Control |
| Volume | 2 |
| Publication status | Published - 2004 |
| Externally published | Yes |
| Event | 2004 43rd IEEE Conference on Decision and Control (CDC) - Nassau, Bahamas Duration: 14 Dec 2004 → 17 Dec 2004 |