An iterative two-level optimization method for the modeling of wiener structure nonlinear dynamic soft sensors

Industrial and Engineering Chemistry Research

Volumn 53, Issue 3, 2014, Pages 1172-1178

  Gao, Xinqing ^a,b   Yang, Fan ^a,b   Huang, Dexian ^a,b   Ding, Yanjun ^a  

^a TSINGHUA UNIVERSITY   (China)

^b TSINGHUA NATIONAL LABORATORY FOR INFORMATION SCIENCE AND TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL COSTS; DYNAMIC SOFT SENSOR; ESSENTIAL DYNAMICS; FINITE-IMPULSE RESPONSE; INDUSTRIAL CASE STUDY; PROCESS INDUSTRIES; TWO-LEVEL OPTIMIZATION; WIENER STRUCTURES;

ITERATIVE METHODS;

SENSORS;

EID: 84892975847     PISSN: 08885885     EISSN: 15205045     Source Type: Journal    
DOI: 10.1021/ie4020793     Document Type: Article

References (18)

1. Kadlec, P.; Gabrys, B.; Strandt, S. Data-driven Soft Sensors in the process industry Comput. Chem. Eng. 2009, 33 (4) 795-814
2. Zamprogna, E.; Barolo, M.; Seborg, D. E. Optimal selection of soft sensor inputs for batch distillation columns using principal component analysis J. Process Control 2005, 15 (1) 39-52
3. Li, W.; Yue, H. H.; Valle-Cervantes, S.; Qin, S. J. Recursive PCA for adaptive process monitoring J. Process Control 2000, 10 (5) 471-486
4. Shi, J.; Liu, X.-G. Melt index prediction by neural soft-sensor based on multi-scale analysis and principal component analysis Chin. J. Chem. Eng. 2005, 13 (6) 849-852
5. Facco, P.; Doplicher, F.; Bezzo, F.; Barolo, M. Moving average PLS soft sensor for online product quality estimation in an industrial batch polymerization process J. Process Control 2009, 19 (3) 520-529
6. Ahmed, F.; Nazir, S.; Yeo, Y. K. A recursive PLS-based soft sensor for prediction of the melt index during grade change operations in HDPE plant Korean J. Chem. Eng. 2009, 26 (1) 14-20
7. Sharmin, R.; Sundararaj, U.; Shah, S.; Vande Griend, L.; Sun, Y.-J. Inferential sensors for estimation of polymer quality parameters: Industrial application of a PLS-based soft sensor for a LDPE plant Chem. Eng. Sci. 2006, 61 (19) 6372-6384
8. Dai, X.; Wang, W.; Ding, Y.; Sun, Z. "Assumed inherent sensor" inversion based ANN dynamic soft-sensing method and its application in erythromycin fermentation process Comput. Chem. Eng. 2006, 30 (8) 1203-1225
9. Rahimpour, M.; Shayanmehr, M.; Nazari, M. Modeling and simulation of an industrial ethylene oxide (EO) reactor using artificial neural networks (ANN) Ind. Eng. Chem. Res. 2011, 50 (10) 6044-6052
10. Yan, W. W.; Shao, H. H.; Wang, X. F. Soft sensing modeling based on support vector machine and Bayesian model selection Comput. Chem. Eng. 2004, 28 (8) 1489-1498
11. Desai, K.; Badhe, Y.; Tambe, S. S.; Kulkarni, B. D. Soft-sensor development for fed-batch bioreactors using support vector regression Biochem. Eng. J. 2006, 27 (3) 225-239
12. Gu, Y.; Zhao, W.; Wu, Z. Online adaptive least squares support vector machine and its application in utility boiler combustion optimization systems J. Process Control 2011, 21 (7) 1040-1048
13. Tangirala, A. K.; Li, D.; Patwardhan, R.; Shah, S. L.; Chen, T. Issues in multirate process control, Proceedings of the 1999 American Control Conference, San Diego, CA, June 2-4, 1999; IEEE: Piscataway, NJ, 1999; pp 2771-2775.
14. Ding, F.; Chen, T. Combined parameter and output estimation of dual-rate systems using an auxiliary model Automatica 2004, 40 (10) 1739-1748
15. Wu, Y.; Luo, X. A novel calibration approach of soft sensor based on multirate data fusion technology J. Process Control 2010, 20 (10) 1252-1260
16. Du, D.; Wu, C.; Luo, X.; Zuo, X. Delay time identification and dynamic characteristics study on ANN soft sensor, Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications, Jinan, China, October 16-18, 2006; IEEE Computer Society: Los Alamitos, CA, 2006; pp 42-45.
17. Lu, W.; Yang, Q.; Huang, D.; Jin, Y. A dynamic soft-sensing method based on impulses response template and parameter estimation with modified DE optimization, Proceedings of the 17th IFAC World Congress, Seoul, Korea, 2008; pp 10983-10988.
18. Chang, C.-C.; Lin, C.-J. LIBSVM: A library for support vector machines ACM Transactions on Intelligent Systems and Technology (TIST) 2011, 2 (3) 27