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.
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页码：134 / 144
页数：11
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