基于事件的网络模糊系统在 DoS 攻击下的改进型故障检测滤波器

IF 3.4 2区 工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC
Di Lun , Huiyan Zhang , Yongchao Liu , Ning Zhao , Wudhichai Assawinchaichote
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引用次数: 0

摘要

本文针对拒绝服务(DoS)攻击下的网络模糊系统,研究了一种改进的基于事件的故障检测方法。为了解决通信网络的带宽占用问题,本文开发了一种弹性事件触发传输策略。此外,还设计了一种故障检测滤波器,利用残差信号估计故障发生的时间。在此框架下,建立了与攻击参数相关的新型 Lyapunov 函数来分析误差信号的指数收敛性,并通过求解线性矩阵不等式获得滤波器增益和事件触发参数。与之前的非连续 Lyapunov 函数相比,所设计的函数大大降低了稳定性标准的保守性。最后,我们提供了一个仿真实例来验证所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Improved event-based fault detection filter for networked fuzzy systems under DoS attacks

This paper investigates an improved event-based fault detection method for networked fuzzy systems under denial-of-service (DoS) attacks. In order to solve the bandwidth occupation problem of communication network, a resilient event-triggered transmission strategy is developed. Additionally, a fault detection filter is designed to estimate the time of fault occurrence by using the residual signal. Under this framework, a novel Lyapunov functional related to attack parameters is established to analyze the exponential convergence of the error signals, and the filter gains and event-triggered parameters are obtained by solving linear matrix inequalities. The designed functional reduces the conservatism of the stability criteria significantly in contrast with the previous discontinuous Lyapunov functionals. Finally, a simulation example is provided to verify the effectiveness of the proposed method.

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来源期刊
Signal Processing
Signal Processing 工程技术-工程:电子与电气
CiteScore
9.20
自引率
9.10%
发文量
309
审稿时长
41 days
期刊介绍: Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing. Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.
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