Nonlinear Inferential Parallel Cascade Control

Industrial and Engineering Chemistry Research

Volumn 35, Issue 1, 1996, Pages 130-137

  Mc Avoy, Thomas J ^a   Ye, Nan ^a   Gang, Chen ^a  

^a UNIVERSITY OF MARYLAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CHEMICAL PLANTS; COMPOSITION; DISTILLATION COLUMNS; FEEDBACK; NEURAL NETWORKS; NONLINEAR CONTROL SYSTEMS; PROCESS ENGINEERING; SENSORS;

INFERENTIAL SENSING; NONLINEAR PARALLEL CASCADE CONTROL; PARALLEL FEEDBACK LOOP; STEADY STATE MODEL;

CASCADE CONTROL SYSTEMS;

EID: 0029771436     PISSN: 08885885     EISSN: None     Source Type: Journal    
DOI: 10.1021/ie950298f     Document Type: Article

References (22)

1. Brambilla, A.; Semino, D. Nonlinear Filter in Cascade Control Schemes. Ind. Eng. Chem. Res. 1992, 31, 2694-2699.
2. Brambffla, A.; Semino, D.; Scali, C. Design and Control Selection of Cascade Loops in Distillation. Preprints of the IFAC Workshop on Integration of Process Design & Control, Baltimore, MD, June 27-28, 1994, p 171.
3. Downs, J.; Vogel, E. A Plant-Wide Industrial Process Control Problem. Comput. Chem. Eng. 1993, 17, 245-255.
4. Kresta, J.; Macgregor, J.; Marlin, T. Multivariate Statistical Monitoring of Process Operating Performance. Can. J. Chem. Eng. 1991, 69, 35-47.
5. Luyben, W. Parallel Cascade Control. Ind. Eng. Chem. Fundam. 1973, 12, 463-467.
6. Macgregor, J.; Marlin, T.; Kresta, J.; Skagerberg, B. Multivariate Statistical Methods in Process Analysis and Control. Proceedings of the Fourth International Conference on Chemical Process Control, South Padre Island, TX, 1991, 665-672.
7. Mc Avoy, T.; Ye, N. Base Control for the Tennessee Eastman Problem. Comput. Chem. Eng. 1994, 18, 383-413.
8. Mejdell, T.; Skogestad, S. Estimation of Distillation Compositions from Multiple Temperature Measurements Using Partial Least Squares. Ind. Eng. Chem. Res. 1991a, 30, 2543-2555.
9. Mejdell, T.; Skogestad, S. Composition Estimator in a Pilot-Plant Distillation Column Using Multiple Temperatures. Ind. Eng. Chem. Res. 1991b, 30, 2555-2564.
10. Piovoso, M.; Kosanovich, K. Applications of Multivariate Statistical Methods to Process Monitoring and Controller Design. Int. J. Control 1994, 59, 743-765.
11. Pottmann, M.; Henson, M.; Ogunnaike, B.; Schwaber, J. A Parallel Control Strategy Abstracted From The Baroreceptor Reflex. Proceedings of the American Control Conference, Baltimore, MD, 1994, pp 97-101.
12. Quin, J.; Mc Avoy, T. Nonlinear PLS Modeling Using Neural Networks. Comput. Chem. Eng. 1992, 16, 379-391.
13. Ricker, N. L. Optimal Steady State Operation of the Tennessee Eastman Challenge Process. Comput. Chem. Eng. 1995, 19, 949-959.
14. Ricker, N. L.; Lee, J. Nonlinear Modeling and State Estimation for the Tennessee Eastman Challenge Process. Comput. Chem. Eng. 1994a, 19, 983-1005.
15. Ricker, N. L.; Lee, J. Nonlinear Model Predictive Control of the Tennesseee Eastman Challenge Process. Comput. Chem. Eng. 1994b, 19, 961-981.
16. Shen, S.; Yu, C. Indirect Feedforward Control: Multivariable Systems. Chem. Eng. Sci. 1992, 47, 3085-3097.
17. Tham, M.; Morris, A.; Montague, G.; Lant, P. Soft Sensors For Process Estimation and Inferential Control. J. Process Control 1991, 1, 3-14.
18. Willis, M.; DiMassimo, C.; Montague, G.; Tham, M.; Morris, A. Inferential Measurements via Artificial Neural Networks. Proceedings of the Symposium on Intelligent Tuning and Adaptive Control, Singapore, 1991.
19. Ye, N. Control of Complex Chemical Processes With Conventional Methods and Neural Networks. Ph.D. Dissertation, University of Maryland, College Park, MD, 1994.
20. Ye, N.; Mc Avoy, T. An Improved Base Control for the Tennessee Eastman Problem. Proceedings of the American Control Conference, Seattle, WA, 1995, pp 240-944,
21. Ye, N.; Mc Avoy, T.; Kosanovich, K.; Piovoso, M. Optimal Averaging Level Control for the Tennessee Eastman Problem. Can. J. Chem. Eng. 1995, 73, 234-240.
22. Yu, C. Design of Parallel Cascade Control for Disturbance Rejection. AIChE J. 1988, 34, 1833-1838.