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On the Robustness of Sampled-Data Systems to Uncertainty in Continuous-Time Delays

机译:连续时间延迟下采样数据系统对不确定性的鲁棒性

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摘要

In this technical note, we consider the robust stability of sampled-data systems with respect to continuous-time delay. We argue that many results in the literature implicitly assume that the delay is a multiple of the sampling period. We demonstrate that this approach might be misleading. Namely, we show that there are systems, which are destabilized by small continuous-time delays despite being delay-independent stable with respect to “integer” delays (this phenomenon has no continuous-time counterpart). We also propose a robustness analysis procedure based on embedding continuous-time delays into unstructured analog uncertainty with the subsequent reduction of the problem to a standard sampled-data $H^{infty}$ problem. Toward this end, a novel nominal model for the uncertain delay is put forward. It yields a tighter unstructured uncertainty covering than in the existing approaches, thus having a potential to reduce the conservatism of the method. This might be advantageous in the pure continuous-time case as well.
机译:在本技术说明中,我们考虑了采样数据系统相对于连续时间延迟的鲁棒稳定性。我们认为,文献中的许多结果都隐含地假设延迟是采样周期的倍数。我们证明这种方法可能会产生误导。即,我们表明存在一些系统,尽管这些系统相对于“整数”延迟而言是独立于延迟的稳定状态,但由于连续时间较小的延迟而不稳定(这种现象没有连续时间的对应物)。我们还提出了一种鲁棒性分析程序,该程序基于将连续时间延迟嵌入到非结构化模拟不确定性中,随后将问题简化为标准采样数据$ H ^ {infty} $问题。为此,提出了一种不确定时延的新型标称模型。与现有方法相比,它具有更紧密的非结构化不确定性覆盖,因此有可能减少该方法的保守性。在纯连续时间情况下,这也可能是有利的。

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