Cyber-security in networked and distributed model predictive control
Autor: | José M. Maestre, P. Chanfreut, T. Arauz |
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Přispěvatelé: | Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática, Universidad de Sevilla. TEP116: Automática y Robótica Industrial |
Rok vydání: | 2022 |
Předmět: | |
Zdroj: | idUS. Depósito de Investigación de la Universidad de Sevilla instname Annual Reviews in Control |
Popis: | Distributed model predictive control (DMPC) schemes have become a popular choice for networked control problems. Under this approach, local controllers use a model to predict its subsystem behavior during a certain horizon so as to find the sequence of inputs that optimizes its evolution according to a given criterion. Some convenient features of this method are the explicit handling of constraints and the exchange of information between controllers to coordinate their actuation and minimize undesired mutual interactions. However, we find that schemes have been developed naively, presenting flaws and vulnerabilities that malicious entities can exploit to gain leverage in cyber-attacks. The goal of this work is to raise awareness about this issue by reviewing the vulnerabilities of DMPC methods and surveying defense mechanisms. Finally, several examples are given to indicate how these defense mechanisms can be implemented in DMPC controllers. Spanish Training Program for Academic Staff FPU19/00127 FPU17/02653 Unión Europea. Horizonte 2020 CONTSOLAR No 789051 Unión Europea, Horizonte 2020 GESVIP US-1265917 Ministerio de Ciencia e Innovación, Agencia Española de Investigación 10.13039/501100011033 C3PO-R2D2 (PID2020-119476RB-I00). |
Databáze: | OpenAIRE |
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