Fixed-Time Bipartite Containment Control for Heterogeneous Multiagent Systems Under DoS Attacks: An Event-Triggered Mechanism

IF 8.6 1区计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS

IEEE Transactions on Systems Man Cybernetics-Systems Pub Date : 2025-01-22 DOI:10.1109/TSMC.2024.3523705

Li Wang;Huaicheng Yan;Xiao Hu;Zhichen Li;Meng Wang

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引用次数: 0

Abstract

This article investigates secure bipartite containment control with the event-triggered mechanism (ETM) for nonlinear heterogeneous multiagent systems (MASs) via the feedback control in fixed time. A novel attacks detection algorithm and an updated label strategy are designed to judge the occurrence of Denial of Service (DoS) attacks or not. It can search for new multiple directed spanning trees for MASs with multiple leaders to decrease the negative influence when attacks happen. In this case, the dynamic ETM is adopted by adjusting the triggered threshold online to save resource consumption. The state-feedback control and output-feedback control are selectively employed according to the situation where the state value of the follower is available or not. The settling time is further relaxed by fixed-time stability theory and can be preset in advance. By theoretical discussion, conditions of achieving bipartite containment control are derived by Lyapunov functions. Finally, the effectiveness of the established control method is verified by simulations.

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DoS 攻击下异构多代理系统的固定时间双部分遏制控制：一种事件触发机制

本文研究了在固定时间内通过反馈控制对非线性异构多代理系统（MASs）进行事件触发机制（ETM）的安全两端遏制控制。文章设计了一种新的攻击检测算法和更新的标签策略，以判断是否发生了拒绝服务（DoS）攻击。它可以为有多个领导者的 MAS 搜索新的多有向生成树，以减少攻击发生时的负面影响。在这种情况下，采用动态 ETM，通过在线调整触发阈值来节省资源消耗。根据跟随者的状态值是否可用，有选择地采用状态反馈控制和输出反馈控制。定时稳定性理论进一步放宽了沉淀时间，并可提前预设。通过理论讨论，利用 Lyapunov 函数推导出实现两端遏制控制的条件。最后，通过仿真验证了所建立的控制方法的有效性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Systems Man Cybernetics-Systems AUTOMATION & CONTROL SYSTEMS-COMPUTER SCIENCE, CYBERNETICS

CiteScore

18.50

自引率

11.50%

发文量

812

审稿时长

6 months

期刊介绍： The IEEE Transactions on Systems, Man, and Cybernetics: Systems encompasses the fields of systems engineering, covering issue formulation, analysis, and modeling throughout the systems engineering lifecycle phases. It addresses decision-making, issue interpretation, systems management, processes, and various methods such as optimization, modeling, and simulation in the development and deployment of large systems.