| 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 | Optim Control Appl 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 |