Resilience Against Replay Attacks: A Distributed Model Predictive Control Scheme for Networked Multi-Agent Systems

• 作者: Giuseppe Franzè Francesco Tedesco Domenico Famularo
• 来源期刊: 自动化学报（英文版）
• 年，卷（期）: 2021,（3）
• 所属期刊栏目: PAPERS
• 页码范围: 628-640
• 页数: 13页
• 语种: 英文
• DOI: 10.1109/JAS.2020.1003542

摘要

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.