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首页> 外文期刊>Applied mathematics and computation >Robust H-infinity stabilization for T-S fuzzy systems with time-varying delays and memory sampled-data control
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Robust H-infinity stabilization for T-S fuzzy systems with time-varying delays and memory sampled-data control

机译:具有时变延迟和内存采样数据控制的T-S模糊系统的鲁棒H-Infinity稳定

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摘要

In this paper, we address the robust H-infinity stabilization for T-S fuzzy systems with time-varying delays based on memory 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 H-infinity 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. (C) 2018 Elsevier Inc. All rights reserved.
机译:在本文中,我们解决了基于内存采样数据控制的时变延迟的T-S模糊系统的鲁棒H-Infinity稳定。 通过开发一些新的术语,构建了一种改进的分段Lyapunov-Krasovskii功能(LKF)以充分利用真实采样模式的特性。 此外,LKF中提出的一些缓解矩阵不一定是正定的。 通过使用基于LKF和自由矩阵(FMB)积分不等式,建立了一些足够的标准,以确保模糊系统的稳定性,并降低外部干扰对H-Infinity Norm的影响。 然后,可以通过求解具有最大采样周期的一组线性矩阵不等式(LMI)来导出存储器采样数据控制器。 最后,给出了数值示例来证明所提出的方法的益处和优越性。 (c)2018年Elsevier Inc.保留所有权利。

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