In this paper, a resilient distributed control scheme against replay attacks for multi-agent networked systems subject to input and state constraints is proposed. The methodological starting point relies on a smart use of predictive arguments with a twofold aim: 1) Promptly detect malicious agent behaviors affecting normal system operations; 2) Apply specific control actions, based on predictive ideas, for mitigating as much as possible undesirable domino effects resulting from adversary operations. Specifically, the multi-agent system is topologically described by a leader-follower digraph characterized by a unique leader and set-theoretic receding horizon control ideas are exploited to develop a distributed algorithm capable to instantaneously recognize the attacked agent. Finally, numerical simulations are carried out to show benefits and effectiveness of the proposed approach.
Scheda prodotto non validato
Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo
|Titolo:||Resilience against Replay Attacks: A Distributed Model Predictive Control Scheme for Networked Multi-Agent Systems|
TEDESCO, Francesco (Corresponding)
|Data di pubblicazione:||2021|
|Appare nelle tipologie:||1.1 Articolo in rivista|