Highly-computational hierarchical iterative identification methods for multiple-input multiple-output systems by using the auxiliary models

被引：5
|
作者：
Xing, Haoming [1 ]
Ding, Feng [1 ,2 ]
Pan, Feng [1 ]
机构：
[1] Jiangnan Univ, Sch Internet Things Engn, Key Lab Adv Proc Control Light Ind, Minist Educ, Wuxi, Peoples R China
[2] Jiangnan Univ, Sch Internet Things Engn, Key Lab Adv Proc Control Light Ind, Minist Educ, Wuxi 214122, Peoples R China
来源：
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL | 2023年 / 33卷 / 17期
基金：
中国国家自然科学基金;
关键词：
computational efficiency; hierarchical identification; least squares; multivariable system; parameter estimation; PARAMETER-ESTIMATION ALGORITHM; FAULT-DIAGNOSIS; OPTIMIZATION; SELECTION; GRADIENT; TRACKING; DELAY;
D O I：
10.1002/rnc.6917
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The identification of multiple-input multiple-output (MIMO) systems is an important part of designing complex control systems. This article studies an auxiliary model least squares iterative (AM-LSI) algorithm for MIMO systems. With the expansion of the system scale and limitations of the computer resources, there is an urgent need for an identification algorithm that provides higher computational efficiency. To address this issue, this article further derives a hierarchical identification model and proposes a new auxiliary model hierarchical least squares iterative (AM-HLSI) algorithm for MIMO systems by applying the hierarchical identification principle. Through the analysis of the computational efficiency, the AM-HLSI algorithm has higher computational efficiency than the AM-LSI algorithm. Additionally, the feasibility of the AM-LSI and AM-HLSI algorithms is validated by a simulation example.
引用
收藏
页码：10845 / 10863
页数：19
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