Secure consensus for PDEs-based multiagent systems under DoS attacks via boundary control approach

IF 6.3 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS ISA transactions Pub Date : 2024-11-01 DOI:10.1016/j.isatra.2024.08.014
Chuanhai Yang , Qingshan Liu
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Abstract

This paper focuses on secure consensus for leader-following multiagent systems (MASs) modeled by partial differential equations (PDEs) under denial of service (DoS) attacks. To mitigate the negative effects of DoS attacks, which can paralyze communication and cause agents to fail to receive valid control inputs, a buffer region is established in the communication channels among agents to temporarily store messages from neighbors. Additionally, since the states of the leader and followers are not always measurable, observers are used to estimate these states. To address these challenges, this paper proposes two boundary controllers to ensure leader-following consensus in both measurable and unmeasurable states. One controller is based on original boundary information, while the other utilizes observation information from both the leader and followers. To the best of our knowledge, this is the first attempt to use buffers to solve a class of PDEs-based MASs under DoS attacks. Furthermore, the boundary control approach has the potential to significantly reduce the number of actuators required, thereby lowering control costs. Finally, we present two numerical examples to validate the feasibility of the proposed methods.
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通过边界控制方法实现基于 PDEs 的多代理系统在 DoS 攻击下的安全共识
本文重点研究了在拒绝服务(DoS)攻击下,由偏微分方程(PDE)建模的领导者跟随型多代理系统(MAS)的安全共识。DoS 攻击会使通信瘫痪,导致代理无法接收有效的控制输入,为了减轻 DoS 攻击的负面影响,我们在代理之间的通信通道中建立了一个缓冲区,以临时存储来自邻居的消息。此外,由于领导者和追随者的状态并不总是可测量的,因此需要使用观测器来估计这些状态。为了应对这些挑战,本文提出了两个边界控制器,以确保领导者和跟随者在可测量和不可测量的状态下达成共识。其中一个控制器基于原始边界信息,而另一个控制器则利用来自领导者和跟随者的观测信息。据我们所知,这是首次尝试在 DoS 攻击下使用缓冲区来解决一类基于 PDE 的 MAS。此外,边界控制方法有可能大大减少所需的执行器数量,从而降低控制成本。最后,我们介绍了两个数值示例,以验证所提方法的可行性。
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来源期刊
ISA transactions
ISA transactions 工程技术-工程:综合
CiteScore
11.70
自引率
12.30%
发文量
824
审稿时长
4.4 months
期刊介绍: ISA Transactions serves as a platform for showcasing advancements in measurement and automation, catering to both industrial practitioners and applied researchers. It covers a wide array of topics within measurement, including sensors, signal processing, data analysis, and fault detection, supported by techniques such as artificial intelligence and communication systems. Automation topics encompass control strategies, modelling, system reliability, and maintenance, alongside optimization and human-machine interaction. The journal targets research and development professionals in control systems, process instrumentation, and automation from academia and industry.
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