Secure consensus for positive multi-agent systems with bumpless transfer control under Denial-of-Service attacks

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS International Journal of Robust and Nonlinear Control Pub Date : 2024-07-30 DOI:10.1002/rnc.7556
Miao Wei, Yijun Zhang, Yang Yuan, Wangli He, Yateendra Mishra, Yu-Chu Tian
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Abstract

This article investigates the secure consensus control problem of positive multi-agent systems under multiple-mode Denial-of-Service (DoS) attacks. A bumpless transfer (BT) control based secure mode strategy is proposed to improve the switching transient performance due to the system being actively switched to secure mode when attack is detected. Considering possible time delays for agents dealing with the issues of DoS attacks, an asynchronous switching model is established between system models and communication topology. With the stability theory of positive systems, sufficient and necessary conditions are established to guarantee the positivity of multi-agent systems under the secure mode strategy. Because the switching law caused by external attacks is unknown in advance, the BT control is specifically implemented through the controller gain interpolation technique. By multiple Lyapunov functions (MLFs) approach, secure consensus is achieved with a trade-off among controller performance, attack parameters, and switching delays. Numerical examples are presented to demonstrate the effectiveness of the obtained results.

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拒绝服务攻击下具有无缓冲转移控制功能的正向多代理系统的安全共识
本文研究了多模式拒绝服务(DoS)攻击下正多代理系统的安全共识控制问题。文章提出了一种基于无缓冲转移(BT)控制的安全模式策略,当检测到攻击时,系统会主动切换到安全模式,从而提高切换的瞬态性能。考虑到代理在处理 DoS 攻击问题时可能出现的时间延迟,在系统模型和通信拓扑之间建立了异步切换模型。利用正向系统的稳定性理论,建立了保证安全模式策略下多代理系统正向性的充分必要条件。由于外部攻击导致的切换规律是事先未知的,因此通过控制器增益插值技术具体实现了 BT 控制。通过多重李亚普诺夫函数(MLFs)方法,在控制器性能、攻击参数和切换延迟之间进行权衡,实现了安全共识。本文列举了一些数值实例来证明所获结果的有效性。
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来源期刊
International Journal of Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control 工程技术-工程:电子与电气
CiteScore
6.70
自引率
20.50%
发文量
505
审稿时长
2.7 months
期刊介绍: Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
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Issue Information Disturbance observer based adaptive predefined-time sliding mode control for robot manipulators with uncertainties and disturbances Issue Information Issue Information A stabilizing reinforcement learning approach for sampled systems with partially unknown models
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