Observer-Based Secure Consensus for Multiagent Systems Under Multimode DoS Attacks With Application to Power System

IF 10.5 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Cybernetics Pub Date : 2025-01-28 DOI:10.1109/TCYB.2025.3528200
Han-Yu Wu;Qingshan Liu;Ju H. Park
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Abstract

This article studies the secure leader-follower consensus of nonlinear multiagent systems under multimode Denial-of-Service attacks. According to the topology characteristics after attacks, three kinds of different attack modes are introduced. Moreover, the common zero-topology attack is encompassed within the multimode attacks considered in this article. Due to the difficulty of directly obtaining the state of the system in some circumstances, a state observer is designed utilizing localized output information of the MASs to estimate the state. By applying suitable observer-based controller and Lyapunov method, some sufficient conditions are presented to ensure the observer-based secure consensus of the MASs under multimode DoS attacks. Furthermore, the obtained results can be extended to linear MASs under DoS attacks. Finally, two practical examples on power system are provided to demonstrate the validity of the derived theoretical results.
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多模式DoS攻击下基于观测器的多智能体系统安全一致性研究及其在电力系统中的应用
研究了非线性多智能体系统在多模式拒绝服务攻击下的安全leader-follower一致性。根据攻击后的拓扑特征,介绍了三种不同的攻击方式。此外,常见的零拓扑攻击包含在本文考虑的多模式攻击中。针对在某些情况下难以直接获取系统状态的问题,设计了状态观测器,利用质量的局部输出信息对系统状态进行估计。通过应用合适的基于观测器的控制器和Lyapunov方法,给出了在多模式DoS攻击下,保证MASs基于观测器的安全一致性的充分条件。此外,所得结果可推广到DoS攻击下的线性质量。最后,通过两个电力系统实例验证了所得理论结果的有效性。
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来源期刊
IEEE Transactions on Cybernetics
IEEE Transactions on Cybernetics COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
25.40
自引率
11.00%
发文量
1869
期刊介绍: The scope of the IEEE Transactions on Cybernetics includes computational approaches to the field of cybernetics. Specifically, the transactions welcomes papers on communication and control across machines or machine, human, and organizations. The scope includes such areas as computational intelligence, computer vision, neural networks, genetic algorithms, machine learning, fuzzy systems, cognitive systems, decision making, and robotics, to the extent that they contribute to the theme of cybernetics or demonstrate an application of cybernetics principles.
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