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首页> 外文期刊>IEEE Transactions on Automatic Control >Continuous-time control model validation using finite experimentaldata
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Continuous-time control model validation using finite experimentaldata

机译：使用有限实验数据的连续时间控制模型验证

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摘要

The application of robust control theory requires models containing unknown, bounded perturbations and unknown, bounded input signals. Model validation is a means of assessing the applicability of a given model with respect to experimental data. This paper develops a theoretical framework, and a computational solution, for the model validation problem in the case where the model, including unknown perturbations and signals, is given in the continuous time domain, yet the experimental datum is a finite, sampled signal. The continuous nature of the unknown components is treated directly with a sampled data lifting theory. This gives results which are valid for any sample period and any datum length. Explicit calculation of whether sufficient data for invalidation has been obtained arises naturally in this framework. A common class of robust control models is treated and leads to a convex matrix optimization problem. A simulation example illustrates the approach
机译：鲁棒控制理论的应用要求模型包含未知的，有界的扰动和未知的，有界的输入信号。模型验证是一种针对实验数据评估给定模型的适用性的方法。本文为模型验证问题开发了一个理论框架和一个计算解决方案，在这种情况下，在连续时域中给出了包括未知扰动和信号在内的模型，而实验数据是有限的采样信号。未知组件的连续性质直接通过采样数据提升理论处理。这样得出的结果对于任何采样周期和任何基准长度均有效。在此框架中自然会明确计算是否已获得足够的无效数据。处理一类常见的鲁棒控制模型，并导致凸矩阵优化问题。仿真示例说明了该方法

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