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Parametric Identification of Hybrid Linear-Time-Periodic Systems

机译:混合线性时间周期系统的参数辨识

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In this paper, we present a state-space system identification technique for a class of hybrid LTP systems, formulated in the frequency domain based on input-output data. Other than a few notable exceptions, the majority of studies in the state-space system identification literature (e.g. subspace methods) focus only on LTI systems. Our goal in this study is to develop a technique for estimating time-periodic system and input matrices for a hybrid LTP system, assuming that full state measurements are available. To this end, we formulate our problem in a linear regression framework using Fourier transformations, and estimate Fourier series coefficients of the time-periodic system and input matrices using a least-squares solution. We illustrate the estimation accuracy of our method for LTP system dynamics using a hybrid damped Mathieu function as an example.
机译:在本文中,我们提出了一种基于输入输出数据的频域公式化的混合LTP系统状态空间系统识别技术。除了少数值得注意的例外,状态空间系统识别文献(例如子空间方法)中的大多数研究都只关注LTI系统。本研究的目标是开发一种用于估计混合LTP系统的时间周期系统和输入矩阵的技术,假设可以使用全状态测量。为此,我们使用傅立叶变换在线性回归框架中阐述问题,并使用最小二乘解估计时间周期系统和输入矩阵的傅立叶级数系数​​。我们以混合阻尼Mathieu函数为例,说明了我们的LTP系统动力学方法的估计精度。

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