Frequency-Domain Subspace Identification of Linear Time-Periodic (LTP) Systems

被引：20

作者：

Uyanik, Ismail ^{[1
]}

Saranli, Uluc ^{[2
]}

Ankarali, Mustafa Mert ^{[3
]}

Cowan, Noah J. ^{[4
]}

Morgul, Omer ^{[5
]}

机构：

[1] Johns Hopkins Univ, Lab Computat Sensing & Robot, Baltimore, MD 21218 USA

[2] Middle East Tech Univ, Dept Comp Engn, TR-06800 Ankara, Turkey

[3] Middle East Tech Univ, Dept Elect & Elect Engn, TR-06800 Ankara, Turkey

[4] Johns Hopkins Univ, Dept Mech Engn, Baltimore, MD 21218 USA

[5] Bilkent Univ, Dept Elect & Elect Engn, TR-06800 Ankara, Turkey

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2019年 / 64卷 / 06期

基金：

美国国家科学基金会;

关键词：

Linear time-periodic (LTP) systems; subspace methods; system identification; time-varying systems; MODEL IDENTIFICATION; ALGORITHMS;

D O I：

10.1109/TAC.2018.2867360

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a new methodology for subspace-based state-space identification for linear time-periodic (LTP) systems. Since LTP systems can be lifted to equivalent linear time-invariant (LTI) systems, we first lift input-output data from an unknown LTP system as if they were collected from an equivalent LTI system. Then, we use frequency-domain subspace identification methods to find the LTI system estimate. Subsequently. we propose a novel method to obtain a time-periodic realization for the estimated lifted LTI system by exploiting the specific parametric structure of Fourier series coefficients of the frequency-domain lifting method. Our method can be used to obtain state-space estimates for unknown LTP systems as well as to obtain Floquet transforms for known LTP systems.

引用

页码：2529 / 2536

页数：8

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