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

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• 作者：Jan Goos ^{jan.goos@vub.ac.be}Author Vitae ; John Lataire ^{john.lataire@vub.ac.be}Author Vitae ; Ebrahim Louarroudi ^{ebrahim.louarroudi@uantwerpen.be}Author Vitae ; Rik Pintelon ^{rik.pintelon@vub.ac.be}Author Vitae
• 关键词：Linear Parameter-Varying systems ; Identification methods
• 刊名：Automatica
• 出版年：2017
• 出版时间：January 2017
• 年：2017
• 卷：75
• 期：Complete
• 页码：191-199
• 全文大小：845 K
• 卷排序：75

文摘

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.