Modeling and control of a continuous crystallization process Part 1. Linear and non-linear modeling

Computers and Chemical Engineering

Volumn 23, Issue 3, 1999, Pages 263-277

  Rohani, S ^a   Haeri, M ^a   Wood, H C ^a  

^a UNIVERSITY OF SASKATCHEWAN   (Canada)

Author keywords

Auto regressive exogenous linear models; Continuous cooling crystallizers; Modeling; Neural network non linear models

Indexed keywords

ALGORITHMS; COMPUTER SIMULATION; CONTROL NONLINEARITIES; CRYSTALLIZERS; FEEDFORWARD NEURAL NETWORKS; INPUT OUTPUT PROGRAMS; INTEGRODIFFERENTIAL EQUATIONS; MATHEMATICAL MODELS; PARTIAL DIFFERENTIAL EQUATIONS; TIME SERIES ANALYSIS; TOPOLOGY;

AUTO REGRESSIVE EXOGENOUS LINEAR MODELS; CONTINUOUS COOLING CRYSTALLIZERS; CRYSTAL SIZE DISTRIBUTION; MULTI INPUT SINGLE OUTPUT MODEL; NEURAL NETWORK NONLINEAR MODELS; SINGLE INPUT SINGLE OUTPUT MODEL;

CRYSTALLIZATION;

COOLING; CRYSTALLIZATION; PROCESS CONTROL;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CRYSTAL STRUCTURE; CRYSTALLIZATION; MOLECULAR MODEL; NONLINEAR SYSTEM; POSITIVE FEEDBACK;

EID: 0033611757     PISSN: 00981354     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0098-1354(98)00271-3     Document Type: Article

References (23)

1. Adomaitis, R. A., Farber, R. M., Hudson, I. L., Kevrekidis, I. G., Kube, M. & Lapedes, A. S. (1993). Application of neural nets to system identification and bifurcation analysis of real world experimental data. (pp. 87-97) Neural Networks: Biological Computers or Electronic Brains. Paris: Springer Verlag.
2. Ashobi, M., (1996). Modeling and Control of a Continuous Crystallization Process Using Neural Networks and Model Predictive Control. Ph.D. thesis, University of Saskatchewan, Saskatoon, Canada.
3. Becraft, W. R., & Lee, P. L. (1993). An integrated neural network/expert system approach for fault diagnosis. Comput. Chem. Engng, 17(10), 1001-1014.
4. Bhat, N., & MacAvoy, T. J. (1990). Use of neural nets for dynamic modeling and control of chemical process systems. Comput. Chem. Engng, 14(4), 573-583.
5. Boutayeb, M., Darouach, M., Rararalahy, H., & Krakala, G. (1993). A new technique for identification of MISO hammerstein model. In Proc. American Control Conf. (1991-1992). San Francisco, CA.
6. Chen, S., Billings, S. A., Cowan, C. F. N., & Grant, P. M. (1990). Practical identification of NARNAX models using radial basis function. Int. J. Control, 52(6), 1327-1350.
7. Chu, S. R., & Shouresi, R. (1993). Neural-based identification of continuous non-linear systems. In Proc. American Control Conf. (pp 1140-1444). San Francisco, CA IEEE Service Center.
8. Gelb, A. (1974). Applied Optimal Estimation. Cambridge, MA: MIT Press.
9. Jerkins, G.M., & Box, G.E.P. (1970). Time Series Analysis, Forecasting and Control. San Fransisco: Holden Day.
10. Jager, J., Kramer, H. J. M., deJong, E. J., deWolf, S., Bosgra, O. H., Boxman, A., Merkus, H. G., & Scarlett, B. (1992). Control of industrial crystallizers. Powder Technol., 69, 11-20.
11. Levin, E., Gewirtzman, R., & Inbar, G. F. (1991). Neural network architecture for adaptive system modeling and control. Neural Networks, 4, 185-191.
12. Narendra, K. S., & Parthasarathy, K. (1990). Identification of control dynamical systems using neural networks. IEEE Trans. Neural Networks, 1, 4-29.
13. Nikolaou, M., & Hanagand, V. (1993). Control of non-linear dynamical systems modeled by recurrent neural networks. A.I.ChE. J. 39(11), 1890-1894.
14. Qin, S. Z., Su, H. T., & McAvoy, T. J. (1992). Comparison of four neural network learning methods for dynamic system identification. IEEE Trans. Neural Network, 3(1), 122-130.
15. Randolph, A., & Larson, M. (1988). Theory of Particulate Systems (2nd Ed.). New York: Marcel Dekker.
16. Rawlings, J. B., Miller, S. M., & Witkowski, R. (1993). Model identification and control of crystallization processes: A review. Ind. Engng. Chem. Res., 32, 1275-1269.
17. Redman, T. P., Rohani, S., & Strathdee, G. (1995). On-line control of supersaturation in a continuous cooling KC1 crystallizer. Can. J. Chem. Engng, 73, 725-733.
18. Rohani, S. (1986). Dynamic study and control of crystal size distribution (CSD) in a KC1 crystallizer. Can. J. Chem. Engng, 64,112-115.
19. Rohani, S. (1995). Crystallization Technology Handbook, Chapter Control of Crystallizers (pp. 327-357). New York: Marcel Dekker.
20. Rohani, S., & Paine, K. (1991). Feedback control of crystal size distribution in a continuous cooling crystallizer. Can. J. Chem. Engng, 69, 165-172.
21. Sudharasanan, S. I., Muhsin, I., & Sundarashan, M. K. (1993). Selftuning adaptive control of mimo non-linear systems using multilayer recurrent neural networks with application to synchronous power generators. In IEEE Int. Conf. Neural Networks (1301-1306). Piscataway, NJ. IEEE Service Center.
22. Taylor, P. A. (1989). MIDSA System Identification and Control Software. Department of Chemical Engineering, McMaster University, Hamilton, Ontario.
23. You, Y., & Nikolaou, M. (1993). Dynamic process modeling with recurrent neural networks. A.I.Ch.E. J. 39(10), 1654-1667.