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
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.
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页数:12
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