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Contraction Mapping Theory and Approach to LMI-Based Stability Criteria of T-S Fuzzy Impulsive Time-Delays Integrodifferential Equations

机译:基于LMI的T-S模糊脉冲时滞积分微分方程稳定性准则的压缩映射理论和方法

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In this paper, Banach fixed point theorem is employed to derive LMI-based exponential stability of impulsive Takagi-Sugeno (T-S) fuzzy integrodifferential equations, originated from Cohen-Grossberg Neural Networks (CGNNs). As far as we know, Banach fixed point theorem is rarely employed to derive LMI criteria for T-S fuzzy CGNNs, and this inspires our present work. It is worth mentioning that the conditions on the behavior functions are weaker than those of existing results, and the formulated contraction mapping and fixed point technique are different from those of previous literature. Even a corollary of our main result improves one of existing main results due to extending linear function to nonlinear function. Besides, the LMI-based criteria are programmable for computer MATLAB LMI toolbox. Moreover, an analytical table and a numerical example are presented to illustrate the advantage, feasibility, and effectiveness of the proposed methods.
机译:本文利用Banach不动点定理推导基于Cohen-Grossberg神经网络(CGNN)的脉冲Takagi-Sugeno(T-S)模糊积分微分方程的基于LMI的指数稳定性。据我们所知,很少使用Banach不动点定理来推导T-S模糊CGNN的LMI标准,这启发了我们目前的工作。值得一提的是,行为函数的条件要比现有结果弱,并且所制定的收缩映射和定点技术与以前的文献不同。由于将线性函数扩展为非线性函数,因此即使是我们的主要结果的推论也可以改善现有的主要结果之一。此外,基于LMI的标准可用于计算机MATLAB LMI工具箱。此外,提供了一个分析表和一个数值示例来说明所提出方法的优点,可行性和有效性。

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