用于机械系统的结构化矢量拟合框架
Structured vector fitting framework for mechanical systems
摘要：
在本文中，我们开发了一个结构保持配方的数据驱动的向量拟合算法的情况下，模态阻尼机械系统。利用模态阻尼二阶系统传递函数的结构极点残数形式，提出了系统传递函数重心公式的两种可能的结构推广。整合这些新的形式内的经典矢量拟合算法导致制定两个新的算法，允许计算模态阻尼机械系统的数据在最小二乘法的方式。因此，保证学习的模型具有期望的结构。我们在两个基准模型上测试了所提出的算法。
英文摘要：
In this paper, we develop a structure-preserving formulation of the data-driven vector fitting algorithm for the case of modally damped mechanical systems. Using the structured pole-residue form of the transfer function of modally damped second-order systems, we propose two possible structured extensions of the barycentric formula of system transfer functions. Integrating these new forms within the classical vector fitting algorithm leads to the formulation of two new algorithms that allow the computation of modally damped mechanical systems from data in a least squares fashion. Thus, the learned model is guaranteed to have the desired structure. We test the proposed algorithms on two benchmark models.
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