This work focuses on the dissipative analysis and quantized sampled-data control design issues for T-S fuzzy networked control system (TSFNCS) under stochastic cyber-attacks (SCAs), which have strong application backgrounds and significant theoretical research value in the field of network security. For this work, a novel time-delay-product relaxed condition (TDPRC) is introduced, which can obtain the slack constraints based on the delay information. Then, by fully considering the delay and sampling time point information, an improved boundary looped-functional (BLF) is developed to acquire more information on the Lyapunov-Krasovskii functional (LKF). In addition, based on the relationship between the sampling moments $(t_{k+1}-t)\eta ^{T}_{3}(t)$ and $(t-t_{k})\eta ^{T}_{4}(t)$ in $V_{c}(x_{t})$, the obtained constraints may be further relaxed. Next, a new criterion and the corresponding algorithm are established using reciprocally convex matrix inequality (RCMI), proper integral inequalities, and the linear convex combination method (LCCM). In addition, a new quantitative sample data (QSD) controller under SCA is designed to ensure that TSFNCS is asymptotically stable (AS) and dissipative. Finally, the experiment of the truck-trailer system (TTS) dynamics equations proves the correctness of the theory proposed in this paper.

中文翻译：

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随机网络攻击下TS模糊NCS的量化采样数据控制策略及其在卡车挂车系统中的应用

本工作重点研究随机网络攻击（SCA）下TS模糊网络控制系统（TSFNCS）的耗散分析和量化采样数据控制设计问题，在网络安全领域具有很强的应用背景和重要的理论研究价值。对于这项工作，引入了一种新的时间延迟产品松弛条件（TDPRC），它可以基于延迟信息获得松弛约束。然后，通过充分考虑延迟和采样时间点信息，开发了一种改进的边界循环泛函（BLF），以获取更多关于Lyapunov-Krasovskii泛函（LKF）的信息。此外，基于采样矩之间的关系$(t_{k+1}-t)\eta ^{T}_{3}(t)$和$(t-t_{k})\eta ^{T}_{4}(t)$在$V_{c}(x_{t})$，得到的约束可以进一步放宽。其次，利用倒易凸矩阵不等式（RCMI）、真积分不等式和线性凸组合法（LCCM）建立了一个新的判据和相应的算法。此外，在 SCA 下设计了一个新的定量样本数据（QSD）控制器，以确保 TSFNCS 是渐近稳定（AS）和耗散的。最后，卡车-拖车系统（TTS）动力学方程的实验证明了本文提出的理论的正确性。