Identification of Time-Varying Systems Using Multi-Wavelet Basis Functions

被引：74

作者：

Li, Yang ^{[1
]}

Wei, Hua-liang ^{[1
]}

Billings, S. A. ^{[1
]}

机构：

[1] Univ Sheffield, Dept Automat Control & Syst Engn, Sheffield S1 3JD, S Yorkshire, England

来源：

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY | 2011年 / 19卷 / 03期

基金：

欧洲研究理事会; 英国工程与自然科学研究理事会;

关键词：

B-splines basis functions; block least mean squares (LMS); normalized least mean squares (LMS); parameter estimation; recursive least squares (RLS); system identification; time variation; FAULT-DETECTION; MODEL;

D O I：

10.1109/TCST.2010.2052257

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 brief introduces a new parametric modelling and identification method for linear time-varying systems using a block least mean square (LMS) approach where the time-varying parameters are approximated using multi-wavelet basis functions. This approach can be applied to track rapidly or even sharply varying processes and is developed by combining wavelet approximation theory with a block LMS algorithm. Numerical examples are provided to show the effectiveness of the proposed method for dealing with severely nonstationary processes. Application of the proposed approach to a real mechanical system indicates better tracking capability of the multi-wavelet basis function algorithm compared with the normalized least squares or recursive least squares routines.

引用

页码：656 / 663

页数：8

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