Parameter Estimation for ARMAX Systems Using Bias Compensation Methods

被引：3
|
作者：
Zhang Yong [1 ]
Cui Gui-mei [1 ]
Liu Xin [1 ]
机构：
[1] Inner Mongolia Univ Sci & Technol, Sch Informat Engn, Baotou 014010, Peoples R China
来源：
CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS | 2009年
关键词：
ARMAX systems; parameter estimation; recursive identification; least squares; bias compensation principle; LEAST-SQUARES IDENTIFICATION; NOISY INPUT;
D O I：
10.1109/CCDC.2009.5194939
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
For ARMAX systems, this paper derives a bias compensation recursive least squares (BCRLS) identification algorithm by means of the prefilter ieda and the bias compensation principle. The proposed algorithm realizes the recursive computation of the bias compensation methods and can be on-line implemented. The BCRLS algorithm can give the unbiased estimation of the system model parameters in the presence of colored noises, irrespective of the noise model. Finally, the advantages of the proposed BCRLS algorithm over the non-recursive bias compensation least squares (BCLS) algorithm are shown by simulation test.
引用
收藏
页码：5029 / 5033
页数：5
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