An iterative least squares estimation algorithm for controlled moving average systems based on matrix decomposition

被引：23
|
作者：
Hu, Huiyi [2 ]
Ding, Feng [1 ,2 ]
机构：
[1] Jiangnan Univ, Control Sci & Engn Res Ctr, Wuxi 214122, Peoples R China
[2] Jiangnan Univ, Minist Educ, Key Lab Adv Proc Control Light Ind, Wuxi 214122, Peoples R China
来源：
APPLIED MATHEMATICS LETTERS | 2012年 / 25卷 / 12期
基金：
中国国家自然科学基金;
关键词：
Least squares; Iterative method; Parameter estimation; Controlled moving average model; STOCHASTIC GRADIENT ALGORITHMS; IDENTIFICATION METHODS; PARAMETER-ESTIMATION; HIERARCHICAL IDENTIFICATION; PERFORMANCE ANALYSIS; CONVERGENCE; EQUATIONS;
D O I：
10.1016/j.aml.2012.06.027
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
An iterative least squares parameter estimation algorithm is developed for controlled moving average systems based on matrix decomposition. The proposed algorithm avoids repeatedly computing the inverse of the data product moment matrix with large sizes at each iteration and has a high computational efficiency. A numerical example indicates that the proposed algorithm is effective. (C) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码：2332 / 2338
页数：7
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