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Title:Scenario based defense mechanism for distributed model predictive control
Authors:P. Velarde, J.M. Maestre, H. Ishii, R.R. Negenborn

Conference:56th IEEE Conference on Decision and Control (CDC2017)
Address:Melbourne, Australia
Date:December 2017

Abstract:In this paper, we present an analysis of the vulnerability of a distributed model predictive control (DMPC) scheme in the context of cyber-security. We consider different types of the so-called insider attacks. In particular, we consider the situation where one of the local controllers sends false information to others to manipulate costs for its own advantage. Then, we propose a popular scenario-based mechanism to protect or, at least, relieve the consequences of the attack in a typical DMPC negotiation procedure. A realistic case study based on a local energy grid of households is provided to illustrate both the consequences of the attacks and the defense mechanisms.

Reference:P. Velarde, J.M. Maestre, H. Ishii, R.R. Negenborn. Scenario based defense mechanism for distributed model predictive control. Accepted for the 56th IEEE Conference on Decision and Control (CDC2017), Melbourne, Australia, December 2017.
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