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Vulnerabilities in Lagrange‐based distributed model predictive control
Author(s) -
Velarde Pablo,
Maestre José M.,
Ishii Hideaki,
Negenborn Rudy R.
Publication year - 2017
Publication title -
optimal control applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.458
H-Index - 44
eISSN - 1099-1514
pISSN - 0143-2087
DOI - 10.1002/oca.2368
Subject(s) - computer science , distributed computing , grid , vulnerability (computing) , insider , controller (irrigation) , model predictive control , computer security , control (management) , information exchange , distributed control system , artificial intelligence , mathematics , telecommunications , agronomy , geometry , political science , law , biology
Summary 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.