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arXiv · 2003.09813

Data-based Receding Horizon Control of Linear Network Systems

Ahmed Allibhoy·Jorge Cortés
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Abstract

We propose a distributed data-based predictive control scheme to stabilize a network system described by linear dynamics. Agents cooperate to predict the future system evolution without knowledge of the dynamics, relying instead on learning a data-based representation from a single sample trajectory. We employ this representation to reformulate the finite-horizon Linear Quadratic Regulator problem as a network optimization with separable objective functions and locally expressible constraints. We show that the controller resulting from approximately solving this problem using a distributed optimization algorithm in a receding horizon manner is stabilizing. We validate our results through numerical simulations.

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Ahmed Allibhoy, Jorge Cortés. 2020-03-22. Data-based Receding Horizon Control of Linear Network Systems. https://doi.org/10.1109/lcsys.2020.3021050

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