Parameter identification of multi-input, single-output systems based on FIR models and least squares principle

被引：29
|
作者：
Ding, Jie [1 ]
Ding, Feng [1 ]
Zhang, Shi [2 ]
机构：
[1] So Yangtze Univ, Jiangnan Univ, Control Sci & Engn Res Ctr, Wuxi 214122, Peoples R China
[2] Nanjing Univ Technol, Coll Automat, Nanjing 210009, Peoples R China
来源：
APPLIED MATHEMATICS AND COMPUTATION | 2008年 / 197卷 / 01期
基金：
中国国家自然科学基金;
关键词：
system identification; parameter estimation; least squares; structure determination; multivariable systems;
D O I：
10.1016/j.amc.2007.07.076
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
By means of auxiliary models - finite impulse response (FIR) models, this paper develops an identification algorithm for multi-input, single-output stochastic systems. The basic idea is to estimate the FIR model parameters of each fictitious subsystem (submodel) with the FIR model orders increasing, and to use auxiliary models to predict/estimate the outputs of the submodels, and further to use the Pade approximation method to produce the parameter estimates of submodels. Some simulation results are given. (C) 2007 Elsevier Inc. All rights reserved.
引用
收藏
页码：297 / 305
页数：9
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