Continuous-time control model validation using finite experimental data
Continuous-time control model validation using finite experimental data
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DOI：
10.1109/9.533673
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发表时间：
1996-08-01
影响因子：
6.8
通讯作者：
Dullerud, GE
中科院分区：
文献类型：
--
作者：
Smith, R;Dullerud, GE
鲁棒控制理论的应用要求模型中含有未知有界扰动和未知有界输入信号。模型验证是根据实验数据来评估给定模型的适用性的一种手段。本文针对模型中含有未知扰动和信号，在连续时间域中给出，而实验数据是有限的采样信号，未知分量的连续性质直接用采样数据提升理论处理，这给出了对任何采样周期和任何数据长度都有效的结果，在此框架下，很自然地产生了是否已获得足够的失效数据的显式计算。一类常见的鲁棒控制模型被处理，并导致凸矩阵优化问题，一个仿真例子说明了该方法。
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.