Iterative identification of output error model for industrial processes with time delay subject to colored noise

Shijian Dong; Tao Liu; Mingzhong Li; Yi Cao

doi:10.1016/j.cjche.2015.08.021

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Iterative identification of output error model for industrial processes with time delay subject to colored noise

第25届中国过程控制会议专栏 | Updated：2026-01-06

- Iterative identification of output error model for industrial processes with time delay subject to colored noise
- Iterative identification of output error model for industrial processes with time delay subject to colored noise
- 中国化学工程学报（英文版） 2015年23卷第12期页码：2005-2012
- Affiliations：
  
  1. 2 Leicester School of Pharmacy, De Montfort University,Leicester,UK,LE1 9BH
  2. 3 School of Energy, Environment and Agrifood, Cranfield University, Cranfield,UK,MK43 0AL
- Author bio：
- Funds：
- DOI：10.1016/j.cjche.2015.08.021
  中图分类号：
- 纸质出版：2015
- Accepted：
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Shijian Dong, Tao Liu, Mingzhong Li, 等. Iterative identification of output error model for industrial processes with time delay subject to colored noise[J]. 中国化学工程学报（英文版）, 2015,23(12):2005-2012.

Shijian Dong, Tao Liu, Mingzhong Li, Yi Cao. Iterative identification of output error model for industrial processes with time delay subject to colored noise[J]. Chin.J.Chem.Eng., 2015, 23(12): 2005-2012.
Shijian Dong, Tao Liu, Mingzhong Li, 等. Iterative identification of output error model for industrial processes with time delay subject to colored noise[J]. 中国化学工程学报（英文版）, 2015,23(12):2005-2012. DOI： 10.1016/j.cjche.2015.08.021.

Shijian Dong, Tao Liu, Mingzhong Li, Yi Cao. Iterative identification of output error model for industrial processes with time delay subject to colored noise[J]. Chin.J.Chem.Eng., 2015, 23(12): 2005-2012. DOI： 10.1016/j.cjche.2015.08.021.

摘要

Abstract

To dealwith colored noise and unexpected load disturbance in identification of industrial processes with time delay

a bias-eliminated iterative least-squares (ILS) identification method is proposed in this paper to estimate the output error model parameters and time delay simultaneously. An extended observation vector is constructed to establish an ILS identification algorithm. Moreover

a variable forgetting factor is introduced to enhance the convergence rate of parameter estimation. For consistent estimation

an instrumental variable method is given to deal with the colored noise. The convergence and upper bound error of parameter estimation are analyzed. Two illustrative examples are used to show the effectiveness and merits of the proposed method.

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