论文标题
使用信号矩阵模型进行冲动响应识别的实验设计
Experiment design for impulse response identification with signal matrix models
论文作者
论文摘要
本文在最近用作数据驱动的仿真和控制方法的基础的隐式模型表示的背景下，为截短的无限脉冲响应识别制定了一种输入设计方法。确切地说，所考虑的模型由数据（或信号）矩阵的列的线性组合组成。最近使用最大似然方法提出了针对嘈杂数据的情况的最佳组合，此处的目的是优化数据矩阵的输入条目，以便最小化估算的均值误差矩阵。根据实验设计文献中通常考虑的最佳标准得出了一个最小值问题。数值结果展示了通过优化输入实现的改进估计拟合。
This paper formulates an input design approach for truncated infinite impulse response identification in the context of implicit model representations recently used as basis for data-driven simulation and control approaches. Precisely, the considered model consists of a linear combination of the columns of a data (or signal) matrix. An optimal combination for the case of noisy data was recently proposed using a maximum likelihood approach, and the objective here is to optimize the input entries of the data matrix such that the mean-square error matrix of the estimate is minimized. A least-norm problem is derived in terms of the optimality criteria typically considered in the experiment design literature. Numerical results showcase the improved estimation fit achieved with the optimized input.
