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S. Hirche

Publications and source records attributed to S. Hirche.

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Decentralized LQ-Consistent Event-triggered Control over a Shared Contention-based Network

Consider a network of multiple independent stochastic linear systems where, for each system, a scheduler collocated with the sensors arbitrates data transmissions to a corresponding remote controller through a shared contention-based communication network. While the systems are physically independent, their optimal controller design problems may, in general, become coupled, due to network contention, if the schedulers trigger transmissions based on state-dependent events. In this article we propose a class of probabilistic admissible schedulers for which the optimal controllers, with respect to local standard LQG costs, have the certainty equivalence property and can still be determined decentrally. Then, two scheduling policies within this class are introduced; a non-event-based and an event-based, both with an easily adjustable triggering probability at every time step. We then prove that, for each closed-loop system, the event-based scheduler and its optimal controller outperforms the closed-loop system with the non-event-based scheduler and its associated optimal controller. Moreover, we show that, for each closed-loop system, the optimal state estimators for both scheduling policies follows a linear iteration. Finally, we provide a method to regulate the triggering probabilities of the schedulers by maximizing a network utility function.

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Information-constrained Optimal Control of Distributed Systems with Power Constraints

In this paper we address the problem of information-constrained optimal control for an interconnected system subject to one-step communication delays and power constraints. The goal is to minimize a finite-horizon quadratic cost by optimally choosing the control inputs for the subsystems, accounting for power constraints in the overall system and different information available at the decision makers. To this purpose, due to the quadratic nature of the power constraints, the LQG problem is reformulated as a linear problem in the covariance of state-input aggregated vector. The zero-duality gap allows us to equivalently consider the dual problem, and decompose it into several sub-problems according to the information structure present in the system. Finally, the optimal control inputs are found in a form that allows for offline computation of the control gains.

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