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arXiv 1012.2316math.OC
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采样和延迟测量下输入具有延迟和零级保持的非线性镇定

Nonlinear Stabilization under Sampled and Delayed Measurements, and with Inputs Subject to Delay and Zero-Order Hold

Iasson Karafyllis, Miroslav Krstic

摘要:

在网络化控制系统中,采样与输入和输出延迟同时出现。当延迟未被补偿时,通常要求采样周期足够小,延迟足够短,并且对于非线性系统,通常仅实现半周期实际稳定性。例如,严格前馈系统在采样测量下的全局镇定,任意稀疏采样的非完整单稳态的采样数据镇定,以及长时滞网络上的LTI系统的采样数据镇定,都是公开问题。在本文中,我们提出了两个一般性的结果,解决这些例子的特殊情况下的问题。首先,我们提出了任意长的输入和输出延迟下的前向完全系统的全局渐近稳定器,具有任意长的采样周期,并连续应用的控制输入。其次,我们考虑系统的采样测量和控制应用通过零级保持,假设系统是稳定的采样数据反馈下的一些采样周期,然后构建采样数据反馈律,实现全局渐近稳定任意长的输入和测量延迟。所有的结果采用“标称”的反馈法律设计的连续时间系统在没有延迟,结合“预测为基础的”补偿的延迟和采样的效果。

英文摘要:

Sampling arises simultaneously with input and output delays in networked control systems. When the delay is left uncompensated, the sampling period is generally required to be sufficiently small, the delay sufficiently short, and, for nonlinear systems, only semiglobal practical stability is generally achieved. For example, global stabilization of strict-feedforward systems under sampled measurements, sampled-data stabilization of the nonholonomic unicycle with arbitrarily sparse sampling, and sampled-data stabilization of LTI systems over networks with long delays, are open problems. In this paper we present two general results that address these example problems as special cases. First, we present global asymptotic stabilizers for forward complete systems under arbitrarily long input and output delays, with arbitrarily long sampling periods, and with continuous application of the control input. Second, we consider systems with sampled measurements and with control applied through a zero-order hold, under the assumption that the system is stabilizable under sampled-data feedback for some sampling period, and then construct sampled-data feedback laws that achieve global asymptotic stabilization under arbitrarily long input and measurement delays. All the results employ "nominal" feedback laws designed for the continuous-time systems in the absence of delays, combined with "predictor-based" compensation of delays and the effect of sampling.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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