具有混合攻击的多智能体系统的事件触发容错一致性控制

IF 8.6 1区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS
Chun Liu;Bin Jiang;Youmin Zhang;Xiaoqiang Ren;Xiaofan Wang
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引用次数: 0

摘要

在本研究中,研究了非线性多智能体系统(MASs)在物理层同时发生执行器/传感器突发和初期故障以及网络层同时发生欺骗/拒绝服务(DoS)混合攻击时的容错共识控制(FTCC)挑战。为了安全增强和/或安全维护的目的,首先设计了一个基于未知状态和故障解耦的增强估计器,然后开发了一个分布式事件触发的FTCC协议,结合增强状态估计、相邻传感器故障估计和最新成功触发的输出交互,分别实现了对抗敌对攻击和故障的强度。通过构造双指标,结合平均停留时间和攻击频率技术,得到了混合攻击下非线性质量的指数均方一致性准则。最后,概述了仿真,以说明所开发的事件触发FTCC方法的有效性和改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Event-Triggered Fault-Tolerant Consensus Control of Multiagent Systems With Hybrid Attacks
In this study, the fault-tolerant consensus control (FTCC) challenge is investigated for nonlinear multiagent systems (MASs) in the simultaneous occurrence of abrupt and incipient actuator/sensor faults in the physical level and hybrid Deception/Denial-of-Service (DoS) attacks in the cyber level. For security enhancement and/or safety maintenance purposes, an unknown state and fault decoupling-based augmented estimator is first devised, and a distributed event-triggered FTCC protocol is then developed to achieve strength against hostile attacks and faults, respectively, with the incorporation of augmented state estimation, neighboring sensor fault estimation, and latest successfully triggered output interaction. By constructing dual indicators along with average dwelling time and attack frequency technique, criteria of exponential mean-square consensus of the nonlinear MASs subject to hybrid attacks are obtained. In the end, simulation is outlined to illustrate the efficacy and improvements of the developed event-triggered FTCC methodology.
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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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