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.

中文翻译：

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抵御重放攻击的弹性：网络化多代理系统的分布式模型预测控制方案

在本文中，针对输入和状态约束的多智能体网络系统，提出了一种针对重放攻击的弹性分布式控制方案。该方法学的出发点有赖于巧妙地使用预测参数，其目的有两个：1）及时检测影响正常系统操作的恶意代理行为；2）根据预测思想采取特定的控制措施，以尽可能减少对手作战造成的不良多米诺效应。具体而言，多主体系统由具有唯一领导者特征的领导者跟随者拓扑图描述，并且利用集理论后退水平控制思想来开发能够即时识别受攻击主体的分布式算法。最后，