Performance analysis of the auxiliary model-based least-squares identification algorithm for one-step state-delay systems

被引：60
作者：
Ding, Feng [1 ,2 ]
Gu, Ya [1 ]
机构：
[1] Jiangnan Univ, Minist Educ, Key Lab Adv Proc Control Light Ind, Wuxi 214122, Peoples R China
[2] Jiangnan Univ, Control Sci & Engn Res Ctr, Wuxi 214122, Peoples R China
来源：
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS | 2012年 / 89卷 / 15期
基金：
中国国家自然科学基金;
关键词：
parameter estimation; recursive identification; state-space model; auxiliary model identification; least squares; PARAMETER-ESTIMATION ALGORITHM; MOVING AVERAGE SYSTEMS; MULTIRATE SYSTEMS; ITERATIVE METHOD; GRADIENT; CONVERGENCE; EQUATIONS;
D O I：
10.1080/00207160.2012.698008
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
Based on the input-output representation of one-step state-delay systems, we use the auxiliary model-based recursive least-squares algorithm to estimate the parameters of the systems and study the convergence of the proposed algorithm by using the stochastic process theory. A simulation example is provided.
引用
收藏
页码：2019 / 2028
页数：10
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