广西师范大学学报（自然科学版） ›› 2026, Vol. 44 ›› Issue (5): 122-134.doi: 10.16088/j.issn.1001-6600.2025111901

• 数学与统计学 • 上一篇    下一篇

基于混合攻击的T-S模糊系统的动态量化控制

梁彩虹1,2, 汪海玲1,2*   

  1. 1.广西师范大学 数学与统计学院, 广西 桂林 541006;
    2.广西应用数学中心(广西师范大学), 广西 桂林 541006
  • 收稿日期:2025-11-19 修回日期:2025-12-26 出版日期:2026-09-05 发布日期:2026-07-24
  • 通讯作者: 汪海玲(1980—), 女, 湖北黄冈人, 广西师范大学教授, 博士。E-mail: wanghl@gxnu.edu.cn
  • 基金资助:
    国家自然科学基金(12461099)

Dynamic quantization control for T-Sfuzzy NCSs under hybrid attacks

Liang Caihong1,2, Wang Hailing1,2*   

  1. 1. School of Mathematics and Statistics, Guangxi Normal University, Guilin Guangxi 541006, China;
    2. The Center for Applied Mathematics of Guangxi (Guangxi Normal University), Guilin Guangxi 541006, China
  • Received:2025-11-19 Revised:2025-12-26 Online:2026-09-05 Published:2026-07-24

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1

摘要： 针对网络带宽受限的T-S模糊系统,本文提出一种基于动态量化与改进记忆事件触发机制的H∞控制策略。首先,为减轻网络传输负担,引入动态量化器,对系统状态进行量化;其次,设计包含历史传输状态信息的记忆事件触发机制,进一步减少非必要数据传输;再次,考虑在网络通信中可能遭受非周期性拒绝服务攻击以及欺骗攻击,构建混合攻击模型,并建立包含攻击频率与持续时间约束的稳定性判据, 进而设计充分利用历史信息的控制器,控制器增益矩阵与事件触发条件的权重矩阵可通过线性矩阵不等式求解,实现控制器增益与量化参数、触发阈值及攻击特性协同优化,在此基础上,构造Lyapunov-Krasovskii泛函,推导出保证闭环系统渐近稳定且满足预设H∞性能的稳定性判据;最后,通过仿真案例验证所提方法的有效性。

关键词: 动态量化, 改进记忆事件触发机制, DoS攻击, 欺骗攻击, T-S模糊系统

Abstract: A control strategy integrating dynamic quantization and an improved memory event-triggered mechanism is proposed for T-S fuzzy systems subject to limited network bandwidth. Firstly, in order to decrease the burden of network transmission, a dynamic quantizer is introduced to process system states. Secondly, a memory event-triggered mechanism incorporating historically transmitted data is designed to further minimize unnecessary data transmissions. Taking into account that aperiodic denial-of-service (DoS) attacks and deception attacks may occur during network communication, a hybrid attack model is established, with explicit conditions on the maximum allowable attack frequency and duration derived. A controller making full use of historical information is designed, in which the controller gain matrices and the weight matrices of the event-triggering condition are obtained using linear matrix inequality (LMI) techniques, thereby achieving co-optimization of controller gains with quantization parameters, triggering thresholds, and attack characteristics. Subsequently, a Lyapunov-Krasovskii functional is constructed, and sufficient conditions are derived to ensure the asymptotic stability of the closed-loop system while satisfying the prescribed H∞ performance. Lastly, a numerical example is provided to illustrate the effectiveness of the proposed control strategy.

Key words: dynamic quantization, improved memory event-triggered mechanism (IMETM), DoS attacks, deception attacks, T-S fuzzy systems

中图分类号:  TP13

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[1] 高钰博, 叶钊显, 黄帅, 周霞, 成军. 网络攻击下具有Markov切换拓扑的多智能体系统的一致性[J]. 广西师范大学学报（自然科学版）, 2025, 43(2): 168-178.
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