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首页> 外文期刊>Cybernetics, IEEE Transactions on >An Improved Fuzzy Sampled-Data Control to Stabilization of T–S Fuzzy Systems With State Delays
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An Improved Fuzzy Sampled-Data Control to Stabilization of T–S Fuzzy Systems With State Delays

机译:一种改进的模糊采样数据控制与状态延迟的T-S模糊系统稳定

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This paper deals with the issue of sampled-data stabilization for T-S fuzzy systems (TSFSs) with state delays and nonuniform sampling. First, a fuzzy membership function (FMFs)-dependent approach is proposed, which uses information not only on both the delayed state and actual sampling pattern but also on the FMFs. Second, the inner sampling interval is split into flexible terminals, and a novel FMFs-dependent Lyapunov-Krasovskii functional (LKF) is constructed. Meanwhile, a fuzzy sampled-data controller (FSDC) with a switched topology is designed to solve the tricky issue on the estimation of FMFs-dependent terms. Then, based on the LKF methodology, the extended Wirtinger's inequality, and an improved reciprocally convex combination strategy, some relaxed criteria with both a larger sampling period and upper bound of time delays for achieving the stabilization of TSFSs are derived. Two numerical examples are presented to demonstrate the superiority and applicability of the proposed scheme.
机译:本文涉及具有状态延迟和非均匀采样的T-S模糊系统(TSFS)的采样数据稳定问题。首先,提出了一种模糊的成员资格函数(FMFS) - 依赖性方法,该方法不仅在延迟状态和实际采样模式上使用信息,而且还在FMF上使用信息。其次,内部采样间隔被分成柔性端子,并且构建了一种新的FMFS依赖性Lyapunov-Krasovskii功能(LKF)。同时,具有交换拓扑的模糊采样数据控制器(FSDC)旨在解决依赖于FMFS依赖项的棘手问题。然后,推导出基于LKF方法,扩展丝杠的不等式,以及改进的互换组合策略,具有较大的采样周期和用于实现TSFS稳定的延迟的较大采样周期和上限的一些缓解标准。提出了两种数值例证以证明所提出的方案的优越性和适用性。

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