Robust Stability for Uncertain Fuzzy Systems with Time-delay Based on Sampled-Data Control

Chao Ge, Ganlei Zhang, Jiaping Tian, Hanxiao Zhao
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Abstract

In this paper, we address the robust stability for un-certain fuzzy systems with time-varying delays based on sampled-data control. By developing some new terms, an improved piecewise Lyapunov-Krasovskii functional (LKF) is constructed to take full advantage of characteristic about real sampling pattern. Furthermore, some relaxed matrices proposed in the LKF are not necessarily positive definite. By using the LKF and Free-Matrix-Based (FMB) integral inequality, some sufficient criteria are established to ensure the stability of fuzzy systems and reduce the influence of external disturbance with an $\mathcal{H}_{\infty}$ norm bound. Then, the memory sampled-data controller can be derived by solving a group of linear matrix inequalities (LMIs) with the maximal sampling period. Finally, a numerical example is given to demonstrate the benefits and the superiority of the approach proposed.
基于采样数据控制的不确定模糊时滞系统鲁棒稳定性
研究了基于采样数据控制的不确定时变时滞模糊系统的鲁棒稳定性问题。通过引入一些新项,构造了一种改进的分段Lyapunov-Krasovskii泛函(LKF),充分利用了真实采样模式的特征。此外,在LKF中提出的一些松弛矩阵不一定是正定的。利用LKF和基于自由矩阵(Free-Matrix-Based, FMB)的积分不等式,以$\mathcal{H}_{\infty}$范数界建立了保证模糊系统稳定性和减小外部干扰影响的充分准则。然后,通过求解具有最大采样周期的一组线性矩阵不等式(lmi),推导出存储器采样数据控制器。最后,通过一个算例说明了该方法的优越性和优越性。
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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