Vulnerabilities in Lagrange-based distributed model predictive control

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

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

14 Citations (Scopus)


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
Issue number2
Publication statusPublished - 2018

Bibliographical note

Special Issue "Global and Robust Optimization of Dynamic Systems"


  • optimal control applications
  • predictive control
  • robust control


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