Frequency domain weighted nonlinear least squares estimation of parameter-varying differential equations

被引：12

作者：

Goos, Jan ^{[1
]}

Lataire, John ^{[1
]}

Louarroudi, Ebrahim ^{[1
]}

Pintelon, Rik ^{[1
]}

机构：

[1] Vrije Univ Brussel, ELEC, Pl Laan 2, B-1050 Brussels, Belgium

来源：

AUTOMATICA | 2017年 / 75卷

关键词：

Linear Parameter-Varying systems; Identification methods; CONTINUOUS-TIME; IDENTIFICATION; SYSTEMS;

D O I：

10.1016/j.automatica.2016.09.031

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 presents a frequency domain identification technique for estimation of Linear Parameter Varying (LPV) differential equations. In a band-limited setting, it is shown that the time derivatives of the input and output signals can be computed exactly in the frequency domain, even for non-periodic inputs and parameter variations. The method operates in an errors-in-variables framework (noisy input and output), but the scheduling signal is assumed to be known. Under these conditions, the proposed estimator is proven to be consistent. (C) 2016 Elsevier Ltd. All rights reserved.

引用

页码：191 / 199

页数：9

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