双网络攻击下非线性随机多智能体系统的动态事件触发一致性跟踪控制

IF 3.1 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS International Journal of Robust and Nonlinear Control Pub Date : 2024-10-17 DOI:10.1002/rnc.7678
Shuangyun Xing, Minghao Li, Feiqi Deng
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引用次数: 0

摘要

研究了非线性随机多智能体系统在DoS攻击和欺骗攻击下的一致性跟踪控制问题。上述攻击分别描述为接收重复数据和接收虚假数据。为了节约网络资源,本研究提出了一种合适的动态事件触发机制。在此基础上,设计了共识跟踪的反馈控制器。在此基础上,提出了双网络攻击下的共识跟踪准则。此外,通过选取新的Lyapunov-Krasovskii泛函和利用Jesen不等式,得到了系统均方稳定的充分条件。最后,通过数值算例验证了该方法的有效性。
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Dynamic Event-Triggered Consensus Tracking Control for Nonlinear Stochastic Multi-Agent Systems Under Dual Network Attacks

This study discusses consensus tracking control problems for nonlinear stochastic multi-agent systems under DoS attacks and deception attacks. The above attacks are respectively described as receiving duplicate data and receiving false data. In an effort to save network resources, this study proposes an appropriate dynamic event-triggered mechanism. On this basis, a feedback controller for consensus tracking is designed. Then, a new consensus tracking criterion under dual network attacks is proposed. In addition, by selecting a new Lyapunov–Krasovskii functional and using Jesen inequality, sufficient conditions for system mean-square stability are obtained. Finally, the efficacy of this approach is validated through a numerical example.

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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.
期刊最新文献
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