Detection and Mitigation of Corrupted Information in Distributed Model Predictive Control Based on Resource Allocation

TL;DR

This paper introduces a monitoring scheme to detect and mitigate communication attacks in distributed model predictive control systems, demonstrated through temperature control simulations under power scarcity.

Contribution

It presents a novel monitoring approach for attack detection and mitigation in distributed predictive control based on resource allocation.

Findings

Effective detection of communication attacks in simulations.

Improved control performance under attack conditions.

Demonstrated robustness of the proposed scheme.

Abstract

In distributed predictive control structures, communication among agents is required to achieve a consensus and approach an optimal global behavior. Such negotiation mechanisms are sensitive to attacks on these exchanges. This paper proposes a monitoring scheme that detects and mitigates these attacks' effects in a resource allocation framework. The performance of the proposed method is illustrated through simulations of the temperature control of multiple rooms under power scarcity.