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Expectation-Maximization Based Defense Mechanism for Distributed Model Predictive Control

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Abstract

Controlling large-scale systems sometimes requires decentralized computation. Communication among agents is crucial to achieving consensus and optimal global behavior. These negotiation mechanisms are sensitive to attacks on those exchanges. This paper proposes an algorithm based on Expectation Maximization to mitigate the effects of attacks in a resource allocation based distributed model predictive control. The performance is assessed through an academic example of the temperature control of multiple rooms under input power constraints.
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Dates and versions

hal-03723298 , version 1 (14-07-2022)

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  • HAL Id : hal-03723298 , version 1

Cite

Rafael Accácio Nogueira, Romain Bourdais, Simon Leglaive, Hervé Guéguen. Expectation-Maximization Based Defense Mechanism for Distributed Model Predictive Control. 9th IFAC Conference on Networked Systems (NecSys22), Jul 2022, Zürich, Switzerland. ⟨hal-03723298⟩
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