多重网络攻击下开关 T-S 模糊系统的动态事件触发 H∞ 控制

IF 3.9 4区计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS

International Journal of Adaptive Control and Signal Processing Pub Date : 2024-08-22 DOI:10.1002/acs.3901

Xiangtong Tan, Xiehuan Li, Guangdeng Zong

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引用次数: 0

摘要

摘要本文研究了开关高木-菅野（Takagi-Sugeno，T-S）模糊系统在多重网络攻击下的动态事件触发控制问题。通过考虑随机虚假数据注入攻击和非周期性拒绝服务攻击，建立了一个新的多重网络攻击模型。然后，为了进一步有效利用网络通信资源，构建了一种包含非负动态变量的动态事件触发机制（ETM）。此外，还利用模型转换方法推导出了考虑动态 ETM 和多重网络攻击的时延切换 T-S 模糊系统。此外，还利用多重 Lyapunov 函数和平均停留时间方法，推导出了全局渐近稳定性和性能的充分条件。最后，举例验证了动态 ETM 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。

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Dynamic event‐triggered H∞ control for switched T‐S fuzzy systems under multiple cyber attacks

SummaryThis article studies the dynamic event‐triggered control problem for switched Takagi‐Sugeno (T‐S) fuzzy systems against multiple cyber attacks. A new multiple cyber attack model is established by considering random false data injection attacks and aperiodic denial‐of‐service attacks. Then, to further efficiently utilize network communication resources, a dynamic event‐triggered mechanism (ETM), which includes a nonnegative dynamic variable, is constructed. Furthermore, the time‐delay switched T‐S fuzzy system considering dynamic ETM and multiple cyber attacks is derived by utilizing model transformation methods. Moreover, sufficient conditions for globally asymptotically stability and performance are derived by utilizing multiple Lyapunov functions and average dwell time method. Finally, an example is provided to validate the effectiveness of dynamic ETM.

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来源期刊

International Journal of Adaptive Control and Signal Processing 工程技术-工程：电子与电气

CiteScore

5.30

自引率

16.10%

发文量

163

审稿时长

5 months

期刊介绍： The International Journal of Adaptive Control and Signal Processing is concerned with the design, synthesis and application of estimators or controllers where adaptive features are needed to cope with uncertainties.Papers on signal processing should also have some relevance to adaptive systems. The journal focus is on model based control design approaches rather than heuristic or rule based control design methods. All papers will be expected to include significant novel material. Both the theory and application of adaptive systems and system identification are areas of interest. Papers on applications can include problems in the implementation of algorithms for real time signal processing and control. The stability, convergence, robustness and numerical aspects of adaptive algorithms are also suitable topics. The related subjects of controller tuning, filtering, networks and switching theory are also of interest. Principal areas to be addressed include: Auto-Tuning, Self-Tuning and Model Reference Adaptive Controllers Nonlinear, Robust and Intelligent Adaptive Controllers Linear and Nonlinear Multivariable System Identification and Estimation Identification of Linear Parameter Varying, Distributed and Hybrid Systems Multiple Model Adaptive Control Adaptive Signal processing Theory and Algorithms Adaptation in Multi-Agent Systems Condition Monitoring Systems Fault Detection and Isolation Methods Fault Detection and Isolation Methods Fault-Tolerant Control (system supervision and diagnosis) Learning Systems and Adaptive Modelling Real Time Algorithms for Adaptive Signal Processing and Control Adaptive Signal Processing and Control Applications Adaptive Cloud Architectures and Networking Adaptive Mechanisms for Internet of Things Adaptive Sliding Mode Control.