Maximum Likelihood Recursive Least Squares Estimation for Multivariable Systems

被引：11

作者：

Li, Junhong ^{[1
]}

Ding, Feng ^{[2
]}

Jiang, Ping ^{[1
]}

Zhu, Daqi ^{[3
]}

机构：

[1] Nantong Univ, Sch Elect Engn, Nantong 226019, Peoples R China

[2] Jiangnan Univ, Sch Internet Things Engn, Wuxi 214122, Peoples R China

[3] Shanghai Maritime Univ, Lab Underwater Vehicles & Intelligent Syst, Shanghai 201306, Peoples R China

来源：

CIRCUITS SYSTEMS AND SIGNAL PROCESSING | 2014年 / 33卷 / 09期

基金：

中国国家自然科学基金;

关键词：

Recursive identification; Multivariable systems; Parameter estimation; Maximum likelihood; STATE-SPACE MODELS; PARAMETER-ESTIMATION; ESTIMATION ALGORITHMS; IDENTIFICATION;

D O I：

10.1007/s00034-014-9783-8

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This paper discusses parameter estimation problems of the multivariable systems described by input-output difference equations. We decompose a multivariable system to several subsystems according to the number of the outputs. Based on the maximum likelihood principle, a maximum likelihood-based recursive least squares algorithm is derived to estimate the parameters of each subsystem. Finally, two numerical examples are provided to verify the effectiveness of the proposed algorithm.

引用

页码：2971 / 2986

页数：16

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