Estimation of catalytic activity using an unscented Kalman filtering in condensation reaction

Wentao Cang; Huizhong Yang

doi:10.1016/j.cjche.2015.11.008

Your Location：

Home >

Browse articles >

Estimation of catalytic activity using an unscented Kalman filtering in condensation reaction

第25届中国过程控制会议专栏 | Updated：2026-01-06

- Estimation of catalytic activity using an unscented Kalman filtering in condensation reaction
- Chinese Journal of Chemical Engineering Vol. 23, Issue 12, Pages: 1965-1969(2015)
- Affiliations：
  
  Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education, Jiangnan University,Wuxi,China,214122
- Author bio：
- Funds：
- DOI：10.1016/j.cjche.2015.11.008
  CLC：
- Published：2015
- Accepted：
Scan QR Code
Wentao Cang, Huizhong Yang. Estimation of catalytic activity using an unscented Kalman filtering in condensation reaction[J]. Chin.J.Chem.Eng., 2015, 23(12): 1965-1969.
DOI：

Wentao Cang, Huizhong Yang. Estimation of catalytic activity using an unscented Kalman filtering in condensation reaction[J]. Chin.J.Chem.Eng., 2015, 23(12): 1965-1969. DOI： 10.1016/j.cjche.2015.11.008.

摘要

Abstract

The catalytic activity of cation exchange resins will be continuously reduced with its use time in a condensation reaction for bisphenol A (BPA). For online estimation of the catalytic activity

a catalytic deactivation model is studied for a production plant of BPA

state equation and observation equation are proposed based on the axial temperature distribution of the reactor and the acetone concentration at reactor entrance. A hybrid model of state equation is constructed for improving estimation precision. The unknown parameters in observation equation are calculated with sample data. The unscented Kalman filtering algorithm is then used for on-line estimation of the catalytic activity. The simulation results show that this hybrid model has higher estimation accuracy than the mechanism model and the model is effective for production process of BPA.

关键词

Keywords

references

Views

Downloads

CSCD

Alert me when the article has been cited

Submit

Tools

Publicity Resources

Attention-enhanced multi-time scale LSTM for soft sensor modeling of corn starch liquefaction

Hydrodechlorination of trifluoro-trichloroethane to chlorotrifluoroethylene: Revealing the deactivation mechanism and regeneration strategy of Pd-Cu/AC catalyst

Application of kinetics and computational fluid dynamics in pinene isomerization

Active training sample selection and updating strategy for near-infrared model with an industrial application

Data-driven intelligent monitoring system for key variables in wastewater treatment process

Related Author

Du Jian

Zhang Lei

Wang Yu

Li Fan

Li Yi

Tao Jin

Zhang Zhongyi

Zhuang Yu

Related Institution

COFCO Biotechnology Co., Ltd.

Institute of Chemical Process Systems Engineering, School of Chemical Engineering, Dalian University of Technology

State Key Laboratory Breeding Base of Green Chemistry Synthesis Technology, Institute of Industrial Catalysis of Zhejiang University of Technology

State Key Laboratory of Fluorine & Nitrogen Chemicals, Xi'an Modern Chemistry Research Institute

Department of Chemical Engineering, School of Chemistry and Chemical Engineering, State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University

⁰