Title Vulnerabilities in Lagrange-based distributed model predictive control
Authors VELARDE RUEDA, PABLO ANIBAL, Maestre, Jose M. , Ishii, Hideaki , Negenborn, Rudy R.
External publication Si
Means Optim Control Appl Methods
Scope Article
Nature Científica
JCR Quartile 2
SJR Quartile 2
JCR Impact 1.45200
Publication date 01/03/2018
ISI 000427136800013
DOI 10.1002/oca.2368
Abstract In this paper, we present an analysis of the vulnerability of a distributed model predictive control scheme. A distributed system can be easily attacked by a malicious agent that modifies the reliable information exchange. We consider different types of so-called insider attacks. In particular, we analyze a controller that is part of the control architecture that sends false information to others to manipulate costs for its own advantage. We propose a mechanism to protect or, at least, relieve the consequences of the attack in a typical distributed model predictive control negotiation procedure. More specifically, a consensus approach that dismisses the extreme control actions is presented as a way to protect the distributed system from potential threats. Two applications are considered as case studies, ie, an academic example involving the control of a distributed system with a single coupled input and a distributed local electricity grid of households. The results are presented via simulations to illustrate both the consequences of the attacks and the defense mechanisms.
Keywords optimal control applications; predictive control; robust control
Universidad Loyola members

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