Identification of continuous-time models with slowly time-varying parameters

被引：12

作者：

Padilla, A. ^{[1
]}

Garnier, H. ^{[2
]}

Young, P. C. ^{[3
]}

Chen, F. ^{[4
]}

Yuz, J., I ^{[5
]}

机构：

[1] Univ La Frontera, Dept Mech Engn, Francisco Salazar 01145, Chile

[2] Univ Lorraine, CRAN, CNRS, F-54000 Nancy, France

[3] Univ Lancaster, Lancaster Environm Ctr, Syst & Control Grp, Lancaster, England

[4] Wuhan Univ, Dept Automat, Wuhan, Hubei, Peoples R China

[5] Univ Tecn Federico Santa Maria, Dept Elect Engn, Valparaiso, Chile

来源：

CONTROL ENGINEERING PRACTICE | 2019年 / 93卷

关键词：

Recursive methods; Continuous-time model identification; Instrumental variable method; Linear time-varying system; Linear filter methods; SYSTEM-IDENTIFICATION; MODULATING FUNCTIONS; SCHEME;

D O I：

10.1016/j.conengprac.2019.104165

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The off-line estimation of the parameters of continuous-time, linear, time-invariant transfer function models can be achieved straightforwardly using linear prefilters on the measured input and output of the system. The on-line estimation of continuous-time models with time-varying parameters is less straightforward because it requires the updating of the continuous-time prefilter parameters. This paper shows how such on-line estimation is possible by using recursive instrumental variable approaches. The proposed methods are presented in detail and also evaluated on a numerical example using both single experiment and Monte Carlo simulation analysis. In addition, the proposed recursive algorithms are tested using data from two real-life systems.

引用

页数：12

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