A Selective Moving Window Partial Least Squares Method and Its Application in Process Modeling

doi:10.1016/j.cjche.2014.05.012

›› 2014, Vol. 22 ›› Issue (7): 799-804.DOI: 10.1016/j.cjche.2014.05.012

• PROCESS MODEL • 上一篇下一篇

A Selective Moving Window Partial Least Squares Method and Its Application in Process Modeling

Ouguan Xu¹, Yongfeng Fu¹, Hongye Su², Lijuan Li ³

1. Zhijiang College, Zhejiang University of Technology, Hangzhou 310024, China;
2. State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, China;
3. College of Automation and Electrical Engineering, Nanjing University of Technology, Nanjing 210009, China

收稿日期:2013-05-15 修回日期:2013-10-16 出版日期:2014-07-28 发布日期:2014-08-23
通讯作者: Ouguan Xu
基金资助:
Supported by the National Natural Science Foundation of China (61203133, 61203072), and the Open Project Program of the State Key Laboratory of Industrial Control Technology (ICT1214).

A Selective Moving Window Partial Least Squares Method and Its Application in Process Modeling

Ouguan Xu¹, Yongfeng Fu¹, Hongye Su², Lijuan Li ³

1. Zhijiang College, Zhejiang University of Technology, Hangzhou 310024, China;
2. State Key Laboratory of Industrial Control Technology, Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310027, China;
3. College of Automation and Electrical Engineering, Nanjing University of Technology, Nanjing 210009, China

Received:2013-05-15 Revised:2013-10-16 Online:2014-07-28 Published:2014-08-23
Supported by:
Supported by the National Natural Science Foundation of China (61203133, 61203072), and the Open Project Program of the State Key Laboratory of Industrial Control Technology (ICT1214).

摘要/Abstract

摘要： A selective moving window partial least squares (SMW-PLS) soft sensor was proposed in this paper and applied to a hydro-isomerization process for on-line estimation of para-xylene (PX) content. Aiming at the high frequency of model updating in previous recursive PLSmethods, a selective updating strategywas developed. Themodel adaptation is activated once the prediction error is larger than a preset threshold, or themodel is kept unchanged. As a result, the frequency of model updating is reduced greatly,while the change of prediction accuracy is minor. The performance of the proposedmodel is better as compared with that of other PLS-based model. The compromise between prediction accuracy and real-time performance can be obtained by regulating the threshold. The guidelines to determine the model parameters are illustrated. In summary, the proposed SMW-PLS method can deal with the slow time-varying processes effectively.

关键词: SMW-PLS, Hydro-isomerization process, Selective updating strategy, Soft sensor

Abstract: A selective moving window partial least squares (SMW-PLS) soft sensor was proposed in this paper and applied to a hydro-isomerization process for on-line estimation of para-xylene (PX) content. Aiming at the high frequency of model updating in previous recursive PLSmethods, a selective updating strategywas developed. Themodel adaptation is activated once the prediction error is larger than a preset threshold, or themodel is kept unchanged. As a result, the frequency of model updating is reduced greatly,while the change of prediction accuracy is minor. The performance of the proposedmodel is better as compared with that of other PLS-based model. The compromise between prediction accuracy and real-time performance can be obtained by regulating the threshold. The guidelines to determine the model parameters are illustrated. In summary, the proposed SMW-PLS method can deal with the slow time-varying processes effectively.

Key words: SMW-PLS, Hydro-isomerization process, Selective updating strategy, Soft sensor

Ouguan Xu, Yongfeng Fu, Hongye Su, Lijuan Li . A Selective Moving Window Partial Least Squares Method and Its Application in Process Modeling[J]. , 2014, 22(7): 799-804.

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A Selective Moving Window Partial Least Squares Method and Its Application in Process Modeling

A Selective Moving Window Partial Least Squares Method and Its Application in Process Modeling

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