| Title |
Vulnerabilities in Lagrange-based distributed model predictive control |
| Authors |
VELARDE RUEDA, PABLO ANIBAL, Maestre, Jose M. , Ishii, Hideaki , Negenborn, Rudy R. |
| External publication |
Si |
| Means |
OPTIMAL CONTROL APPLICATIONS & METHODS |
| Scope |
Article |
| Nature |
Científica |
| JCR Quartile |
2 |
| SJR Quartile |
2 |
| JCR Impact |
1.452 |
| Publication date |
01/03/2018 |
| ISI |
000427136800013 |
| DOI |
10.1002/oca.2368 |
| 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. |
| Keywords |
optimal control applications; predictive control; robust control |
| Universidad Loyola members |
|
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