Distributed Finite-Time Extended Dissipative Filtering and Event-Triggered Strategy for Nonlinear Systems Over Sensor Networks With Two-Channel Stochastic Attacks

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS
Xin Zhou, Guici Chen, Song Zhu, Xiao-Heng Chang, Mouquan Shen
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引用次数: 0

Abstract

This study delves into the distributed finite-time extended dissipative filtering problem and event-triggered strategy for nonlinear systems over sensor networks with two-channel stochastic deception attacks. A new distributed filter is proposed, which simultaneously addresses the event-triggered strategy and two-channel attack scenario. Here, the event-triggered strategy is devised in a distributed manner, and the deception attack model following the Bernoulli distribution is established. Additionally, the finite-time extended dissipative index is considered to resolve the finite-time distributed H $$ {H}_{\infty } $$ , L 2 L $$ {L}_2-{L}_{\infty } $$ , passive, and dissipative filtering problem within a unified framework. Sufficient conditions are derived to ensure stochastically finite-time extended dissipation for filtering error systems through stochastic analysis and iterative methods. Finally, the numerical simulation example is provided to validate the theoretical results.

双通道随机攻击下传感器网络非线性系统的分布式有限时间扩展耗散滤波和事件触发策略
本研究深入探讨了具有双通道随机欺骗攻击的传感器网络非线性系统的分布式有限时间扩展耗散滤波问题和事件触发策略。研究提出了一种新的分布式滤波器,可同时解决事件触发策略和双通道攻击问题。在这里,以分布式方式设计了事件触发策略,并建立了遵循伯努利分布的欺骗攻击模型。此外,还考虑了有限时间扩展耗散指数,以解决有限时间分布式 H ∞ $$ {H}_{\infty } 的问题。$$ , L 2 - L ∞ $$ {L}_2-{L}_{\infty }.$$ ,被动和耗散滤波问题的统一框架。通过随机分析和迭代方法,得出了确保滤波误差系统随机有限时间扩展耗散的充分条件。最后,提供了数值模拟实例来验证理论结果。
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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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