Vulnerabilities in Lagrange‐based distributed model predictive control

Pablo Velarde; José M. Maestre; Hideaki Ishii; Rudy R. Negenborn

doi:10.1002/oca.2368

Vulnerabilities in Lagrange‐based distributed model predictive control

Journal

Optimal Control Applications and Methods

ISSN

1099-1514

Date Issued

2017-09-27

Author(s)

Pablo Velarde

Facultad de Ciencias de la Ingeniería e Industrias

José M. Maestre

Hideaki Ishii

Rudy R. Negenborn

DOI

10.1002/oca.2368

URL

https://cris.ute.edu.ec/handle/123456789/879

Abstract

SummaryIn 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.