Resilient Finite-Time Consensus of Variable-Order Fractional Multiagent Systems Under DoS Attacks

IF 8.6 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Ruihong Li;Qintao Gan;Huaiqin Wu;Jinde Cao;Qiaokun Kang
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引用次数: 0

Abstract

This article aims to address the finite-time consensus issue for variable-order fractional multiagent systems (MASs) under denial of serve (DoS) attacks. First, the framework of node-based DoS attack is introduced, including its influences, detection, and recovery mechanisms. Second, a new variable-order fractional difference (VO-FD) inequality is proposed to accurately evaluate the variable-order fractional derivative of the power function. Based on the developed inequality, two novel finite-time stability theorems are presented based on the developed inequality, which fill up the gap in variable-order fractional finite-time stability without and with DoS attacks, respectively. Third, a resilient distributed control protocol is proposed, where the dynamic event-triggered mechanism (DETM) is introduced based on the detected signal of attack to ensure the desired control performance and economize system resources. According to the Lyapunov stability theory, the consensus can be achieved within the settling time, and some linear matrix inequality (LMI)-based conditions are obtained. Finally, the feasibility and validity of theoretical analysis is illustrated by simulation example.
DoS 攻击下变序分数多代理系统的弹性有限时间共识
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来源期刊
IEEE Transactions on Systems Man Cybernetics-Systems
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.
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