A Principled Approximation Framework for Optimal Control of Semi-Markov Jump Linear Systems
Saeid Jafari, Ketan Savla

TL;DR
This paper develops a framework for optimal control of semi-Markov jump linear systems by approximating holding-time distributions with phase-type and matrix exponential methods, enabling efficient controller synthesis.
Contribution
It introduces a novel approximation approach for semi-Markov systems using phase-type and matrix exponential methods, facilitating optimal control design with reduced computational complexity.
Findings
Established conditions for optimal controllers in the proposed models.
Proposed matrix exponential approximation reduces computational costs.
Developed techniques to ensure non-negativity of holding-time densities.
Abstract
We consider continuous-time, finite-horizon, optimal quadratic control of semi-Markov jump linear systems (S-MJLS), and develop principled approximations through Markov-like representations for the holding-time distributions. We adopt a phase-type approximation for holding times, which is known to be consistent, and translates a S-MJLS into a specific MJLS with partially observable modes (MJLSPOM), where the modes in a cluster have the same dynamic, the same cost weighting matrices and the same control policy. For a general MJLSPOM, we give necessary and sufficient conditions for optimal (switched) linear controllers. When specialized to our particular MJLSPOM, we additionally establish the existence of optimal linear controller, as well as its optimality within the class of general controllers satisfying standard smoothness conditions. The known equivalence between phase-type…
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Taxonomy
TopicsAdvanced Queuing Theory Analysis · Stability and Control of Uncertain Systems · Simulation Techniques and Applications
