Decomposition based least squares iterative estimation algorithm for two-input single-output output error systems

被引：4
|
作者：
Lu, Xianling [1 ,2 ]
Shi, Wenlin [2 ]
Zhou, Wei [2 ]
机构：
[1] Jiangnan Univ, Key Lab Adv Proc Control Light Ind, Minist Educ, Wuxi 214122, Peoples R China
[2] Jiangnan Univ, Sch Internet Things Engn, Wuxi 214122, Peoples R China
来源：
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS | 2014年 / 351卷 / 12期
关键词：
MOVING AVERAGE SYSTEMS; MODEL-PREDICTIVE CONTROL; TIME NONLINEAR-SYSTEMS; PARAMETER-ESTIMATION; MULTIVARIABLE SYSTEMS; MATRIX EQUATIONS; COLORED NOISE; IDENTIFICATION; STATE; DELAYS;
D O I：
10.1016/j.jfranklin.2014.10.001
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 paper develops a decomposition based least squares iterative identification algorithm for two-input single-output (TISO) systems. The basic idea is to decompose a TISO system into two subsystems and then to identify each subsystem, respectively. Compared with the least squares based iterative algorithm, the proposed algorithm has less computational load. The simulation results indicate that the proposed algorithm is effective. (C) 2014 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：5511 / 5522
页数：12
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