Identification of errors-in-variables ARX model with time varying time delay

被引：3

作者：

Zhang, Jinxi ^{[1
,2
]}

Guo, Fan ^{[2
,3
]}

Hao, Kuangrong ^{[1
]}

Chen, Lei ^{[1
]}

Huang, Biao ^{[2
]}

机构：

[1] Donghua Univ, Coll Informat Sci & Technol, Shanghai 201620, Peoples R China

[2] Univ Alberta, Dept Chem & Mat Engn, Edmonton, AB T6G2G6, Canada

[3] Nanjing Inst Technol, Sch Automat, Nanjing 211167, Peoples R China

来源：

JOURNAL OF PROCESS CONTROL | 2022年 / 115卷

基金：

加拿大自然科学与工程研究理事会; 上海市自然科学基金; 中国国家自然科学基金;

关键词：

Parameter estimation; Time delays; Errors-in-variables (EIV); Expectation maximization algorithm (EM); ROBUST IDENTIFICATION; FAULT-DIAGNOSIS; SYSTEMS; KALMAN; MIXTURE; DESIGN;

D O I：

10.1016/j.jprocont.2022.04.019

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

An identification method is proposed for errors-in-variables (EIV) ARX model with input time-varying time-delays. A Markov chain is used to model varying time delays whose parameters are also estimated. The EIV system accounts for noises in both input and output. To estimate noise-free input, a linear state space model is used to describe input generation process and a Kalman smoother is adopted for its estimation. An expectation maximization algorithm is used to estimate ARX model parameters. A spinning process of polyester fiber and a continuous stirred tank reactor process are used to verify the effectiveness of the proposed approach.(C) 2022 Elsevier Ltd. All rights reserved.

引用

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页码：134 / 144

页数：11

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