Skip to Main content Skip to Navigation
Conference papers

Expectation-Maximization Based Defense Mechanism for Distributed Model Predictive Control

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.
Complete list of metadata

https://hal-centralesupelec.archives-ouvertes.fr/hal-03723298
Contributor : Rafael Accacio Nogueira Connect in order to contact the contributor
Submitted on : Thursday, July 14, 2022 - 12:13:36 PM
Last modification on : Friday, July 22, 2022 - 4:10:30 AM

File

article.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : hal-03723298, version 1

Citation

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⟩

Share

Metrics

Record views

0

Files downloads

0