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Quantized Stabilization for T–S Fuzzy Systems With Hybrid-Triggered Mechanism and Stochastic Cyber-Attacks

机译:带有混合触发机制和随机网络攻击的TS模糊系统的量化镇定

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This paper examines quantized stabilization for Takagi–Sugeno (T–S) fuzzy systems with a hybrid-triggered mechanism and stochastic cyber-attacks. A hybrid-triggered scheme, which is described by a Bernoulli variable, is adopted to mitigate the burden of the network. By taking the effect of the hybrid-triggered scheme and stochastic cyber-attacks into consideration, a mathematical model for a closed-loop control system with quantization is constructed. Theorems for main results are developed to guarantee the asymptotical stability of networked control systems by using Lyapunov stability theory and linear matrix inequality techniques. Based on the derived sufficient conditions in theorems, the controller gains are presented in an explicit form. Finally, two practical examples demonstrate the feasibility of designed algorithm.
机译:本文研究了具有混合触发机制和随机网络攻击的Takagi-Sugeno(TS)模糊系统的量化镇定。采用由伯努利变量描述的混合触发方案来减轻网络的负担。通过考虑混合触发方案和随机网络攻击的影响,构建了带有量化的闭环控制系统的数学模型。利用Lyapunov稳定性理论和线性矩阵不等式技术,开发了主要结果定理,以确保网络控制系统的渐近稳定性。基于定理中得出的充分条件,控制器增益以显式形式表示。最后,两个实例说明了该算法的可行性。

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