Kesikli Bir Polimerizasyon Reaktörüne Farklı Optimal Şartlarda Sıcaklık Kontrolunun Uygulanması

Öz

Genelleştirilmiş öngörmeli kontrol(GPC) ile genelleştirilmiş delta kuralı(GDK) izotermal koşullar altında stirenin polimerizasyonunun gerçekleştiği ceketli kesikli bir reaktörün sıcaklığını kontrol etmede kullanılmıştır. Monomer dönüşümü, viskozite ortalama molekül ağırlığı ve zincir uzunluğu üzerine değişik optimal koşulların etkileri incelenmiştir. Reaktör sıcaklığı ve reaktöre verilen ısı arasındaki etkileşime dayanan yapay sinir ağı modeli kullanılmıştır. GPC’li GDK’nın etkinliği belirlenen sabit sıcaklıklarda GDK parametreleri kullanılarak deneysel ve benzetim ile incelenmiştir. Sonuçlar Self-Tuning PID (STPID) yöntemi ile karsılaştırılmıştır. Kontrol deneyleri sonucunda GDK-GPC kontrol yönteminin iyi bir performans gösterdiği ve istenilen özelliklerde polimer elde edildiği gözlenmiştir. Ayrıca GDK-GPC yönteminin STPID yönteminden daha iyi olduğu hem kontrol performansından hem de elde edilen polimer özelliklerinden gözlenmektedir.

Anahtar Kelimeler

• Polimerizasyon reaktörü, genelleştirilmiş delta kuralı algoritması, genelleştirilmiş öngörülmüş kontrol

APPLICATION OF TEMPERATURE CONTROL IN A BATCH POLYMERIZATION REACTOR AT DIFFERENT OPTIMAL TEMPERATURES

Öz

The generalized delta rule (GDR) algorithm with generalized predictive control (GPC) was used to control the temperature of a jacketed batch reactor in which styrene polymerization occurs under isothermal conditions. The effects of different optimal conditions were examined on monomer conversion, average viscosity molecular weight and chain length. The neural network model based on the relation between the reactor temperature and heat input to the reactor was used. The efficiency of the GDR with GPC was examined by simulation and experimentally using GDR parameters specified at constant temperatures, and compared with Self-Tuning PID (STPID). It was observed that the control experiments provided a good performance in maintaining the reactor temperature at its set point and yielded polymer product with desired properties. 

Anahtar Kelimeler

• Polymerization reactor,generalized delta rule algorithm,generalized predictive control

Kaynakça

1. Barner-Kowollik, C., & Davis, T.P., “Using
2. Kinetics and Thermodynamics in the controlled
3. synthesis of low molecular weight polymers in
4. free-radical polymerization”, Macromol. Theory
5. Simul., 10, 255, 2001.
6. Scali, C., Morretta, M., & Semino, D., “Control of
7. the quality of polymer products in continuous
8. reactors: comparison of performance of state

9. estimators with and without updating of
10. parameters”, J. Proc. Cont., 7, 357, 1997.
11. Erdoğan, S., Alpbaz, M., & Karagöz, A.R., “The
12. effect of operational conditions on the
13. performance of batch polymerization reactor
14. control”, Chem. Eng. J., 86, 259, 2002.
15. Yang, J., Li, X., Mou, H.-G., & Jian, L., “Control-Oriented Thermal Management of Solid Oxide Fuel Cells Based on a Modified Takagi–Sugeno Fuzzy Model”, Journal of Power Sources, 188, 475-482, 2009.
16. Leite, M. S., Santos, B. F., Lona, L. M. F., Silva, F. V., & Fileti, A. M. F., “Application of Artificial Intelligence Techniques for Temperature Prediction in a Polymerization Process”, Chemical Engineering Transactions, 24, 385-
17. , 2011.
18. Richards, J.R. & Congalidis, J.P., “Measurement and control polymerization reactors”, Comput. Chem. Eng., 30, 1447, 2006.
19. Seki, H., Ogawa, M., Ooyama, S., Akamatsu, K., Ohshima, M., & Yang, W., “Industrial application of a nonlinear model predictive control to polymerization reactors”, Cont. Eng. Pract., 9, 819, 2001.
20. Xaumier, F., Lann, M-V.L., Cabassud, M., & Casamatta, G., “Experimental application of nonlinear model predictive control: temperature control of an industrial semi-batch pilot-plant reactor”, J. Proc. Cont., 12, 687, 2002.
21. Altınten, A., Erdoğan, E., Hapoğlu, H., Alıev, F., & Alpbaz, M., “Application of fuzzy control metod with genetic algorithm to a polymerization reactor at constant set point”, Chem. Eng. Res. Des. (IChemE), 84(A11), 1012, 2006.
22. Altınten, A., Erdoğan, E., Hapoğlu, H., & Alpbaz, M., “Control of a polymerization reactor by fuzzy control method with genetic algorithm”, Comp. Chem. Eng., 27, 1031, 2003.
23. Erdoğan, S., Özkan, G., & Alpbaz, M., “Self-Tuning control of batch polymerization reactor”, J. Chem. Eng. Japan, 31, 499, 1998.
24. Lewis, G.T., Nguyen, V., & Cohen, Y., “Synthesis of poly(4-vinylpyridine) by reverse atom transfer radical polymerization”, J. Polym. Sci., 45 (Part A), 5748, 2007.
25. Altınten, A., Ketevanlioğlu, F., Erdoğan, S., Hapoğlu, H., & Alpbaz, M., “Self-tuning PID control of jacketed batch polystyrene reactor using genetic algorithm”, Chem. Eng. J., 138, 490, 2008.
26. Zhang, J., Morris, A.J., Martin, E.B., & Kiparissides, C., “Prediction of polymer quality in batch polymerization reactors using robust neural network”, Chemical Eng. J., 69, 135, 1998.
27. Yang, S.H., Chung, P.W.H., & Brooks, B.W., “Multi-stage modelling of a semi-batch polymerization reactor using artificial neural networks”, Trans IChemE, 77 (Part A), 779, 1999.
28. Zeybek, Z., “Role of adaptive heuristic criticism in cascade temperature control of an industrial tubular furnace”, Applied Thermal Engineering, 26, 152, 2006.
29. Özkan, G., Hapoğlu, H., & Alpbaz, M., “Generalized predictive control of optimal temperature profiles in a polystyrene polymerization reactor”, Chemical Engineering and Processing, 37, 125, 1998.
30. Yüce (Çetinkaya), S., Nonlinear Model Predictive Control of Reactor Temperature in
31. Agitated Batch Polymerization Reactor Operating Optimal Condition, Ph.D Thesis, Department of Chemical Engineering, University of Ankara, Turkey, 2001.
32. Zeybek, Z., Çetinkaya, S., Hapoğlu, H., & Alpbaz, M., “Generalized delta rule (GDR) algorithm with generalized predictive control (GPC) for optimum temperature tracking of batch polymerization”, Chem. Eng. Sci., 61, 6691, 2006.
33. Hsu, K-Y., & Chen, S-A., “Optimal piecewise constant temperature policies for batchwise thermally initiated bulk polymerization of styrene”, Journal of the Chinese Institute of Chemical Engineers, 17(5), 315, 1986.
34. Zaheer-uddin, M., & Tudoroiu, N., “Neuro-PID tracking control of a discharge air temperature system”, Energy Conversion and Management, 45, 2405, 2004.
35. Ekpo, E.E., & Mujtaba, I.M., “Evaluation of neural networks-based controllers in batch polymerization of methyl methacrylate”, Neurocomputing, 71, 1401, 2008.
36. Valigi, P., Fravolini, M.L., & Ficola, A., “Improved temperature control of a batch reactor with actuation constraints”, Cont. Eng. Pract., 14, 783, 2006.
37. Yüce, S., Hasaltun, A., Erdoğan, S., & Alpbaz, M., “Temperature control of a batch polymerization reactor”, Trans IChemE, 77 Part A, 413, 1999.
38. Chen, S.A., & Jeng, W.F., “Minimum end time policies for batch-wise radical polymerization”, Chem Eng Sci., 33, 735, 1978.
39. Karagöz, A.R., Özkan, G., Erdoğan, S., & Alpbaz, M., “Modeling optimization and control of batch polymerization reactors”, Control and Computers, 25(1), 21, 1997.
40. Rumelhart, D.E., Hinton, G.E., & Williams, R.J., “Learning representations by backpropagation errors”, Nature, 323, 533, 1986.
41. Werbos, P., Beyond Regression: New tools for predicting and analysis in the behavioral scienses, Ph.D Thesis, Cambridge, MA: Harvard University Committee on Applied Mathematics, 1974.
42. Parker, D., “Learning-logic”, invention report S81-64, file 1, Office of Technology Licensing, Stanford University, Stanford, CA, 1982.
43. LeCun, Y., “Learning process in an asymmetric threshold network in disordered systems and biological organization”, Les Houches, France, 223, 1986.
44. Widrow, B. & Hoff, M., “Adaptive switching circuits, In Western Electronic Show and Convention”, Institute of Radio Engineers (IEEE), 4, 96, 1960.
45. Lu, Y-Z., Industrial intelligent control, fundamentals and applications, 1. Edition, 1996.
46. Çetinkaya, S., Dynamic matrix control of a batch polymerization reactor under the optimal conditions, M.Sc. Thesis, Department of Chemical Engineering, Ankara University, Turkey, 1996.