Vulnerabilities in Lagrange-based distributed model predictive control

Pablo Velarde, José María Maestre, Hideaki Ishii, Rudy R. Negenborn

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)601-621
JournalOptimal Control Applications and Methods
Volume39
Issue number2
DOIs
Publication statusPublished - 2018

Keywords

  • optimal control applications
  • predictive control
  • robust control

Fingerprint Dive into the research topics of 'Vulnerabilities in Lagrange-based distributed model predictive control'. Together they form a unique fingerprint.

  • Cite this