论文标题
从输入输出数据中学习二次控制系统的减少订购模型
Learning reduced-order models of quadratic control systems from input-output data
论文作者
论文摘要
在本文中，我们介绍了从输入输出数据中学习二次控制系统的Loewner框架的扩展。所提出的方法首先从经典传递函数的测量值构建了降低的线性模型。然后，通过合并一个四边形取决于状态的术语来增强该替代模型。更确切地说，我们采用基于最小二乘拟合的迭代程序，考虑到测量或计算的数据。在这里，当对照输入纯粹振荡时，数据代表从观察到的输出的较高谐波推断出的传递函数值。
In this paper, we address an extension of the Loewner framework for learning quadratic control systems from input-output data. The proposed method first constructs a reduced-order linear model from measurements of the classical transfer function. Then, this surrogate model is enhanced by incorporating a term that depends quadratically on the state. More precisely, we employ an iterative procedure based on least squares fitting that takes into account measured or computed data. Here, data represent transfer function values inferred from higher harmonics of the observed output, when the control input is purely oscillatory.
