DOI: https://doi.org/10.15587/2312-8372.2016.85613

Model predictive control of distillation column in the carbon dioxide recycling in methanol technological process

Виталий Семенович Пастушенко, Алексей Аркадьевич Стопакевич, Андрей Алексеевич Стопакевич

Abstract


The distillation column (DC) was taken as the research object. A homogeneous catalyst is necessary for continuous operation of the column. Considered object is promising for carbon dioxide recycling in the methanol production enterprises, power plants, boiler stations. Modern high-quality model predictive control system is developed for the column. It is a basic unit of the latest technological process of carbon dioxide recycling in the methanol production. Its feature is the ability to take into account the non-linearity and the use of optimization procedure. The controller settings are calculated for DC: P controllers to stabilize levels (for channel D-MD Kp = -2; for channel B-MB Kp = 0,2) and the PI controllers for stabilization of concentrations (for channel L-y D Kp = 2 and Ti = 0,01, for channel V-xB Kp = -30, Ti = 0,1). For a system with MPC were calculated: discrete step (c) = 0,5; prediction horizon = 500; control horizon = 2; balance of stability and speed = 0,8; observer sensitivity = 0,5. Methanol production process was simulated with 2 systems. The comparison results show that the quality of transients in a system with model-predictive control higher when all perturbations, except perturbation over the phase state of the input stream. However, the latter in the above technological process practically does not occur. Use of MPC algorithm can significantly improve the effectiveness of the control system. The developed control system is very good meeting the major perturbation to change the product concentration, which enters the column from the synthesis reactor. System with MPC controller has more quality than a system with PI controller. When implementing the distillation column, an amount of emitted CO2 and use of methanol as a finished product, and as a raw material will by reduced. In the future there is the possibility of applying a model predictive system for other objects and processes to improve the quality of transients.


Keywords


model predictive control; distillation column; technological process; recycling; carbon dioxide; methanol

References


Stopakevich, А., Skakun, N. (2015). О vozmozhnosti primenenija sovremennyh SAPR himiko-tehnologicheskih system dlia sinteza SAU neftianymi rektifikatsionnymi kolonnami, 4 International Scientific Conference «Economics and control in the conditions of informational society growth», Odessa, 27-29.04.2015. Odessa: ONAT, 82–84.

Stopakevich, А., Stopakevich, А. (2015). Synthesis and Research of Supervisory Digital Control System for Oil Distillation Column. Automation of Technological and Business Processes, 4 (7), 24–34.

Veremey, Е., Sotnikova, М. (2014). Upravlenie s prognoziruiushchimi modeliami. Saint-Petersburg: SPBGU, 212.

Huyck, B., De Brabanter, J., De Moor, B., Van Impe, J. F., Logist, F. (2014). Online model predictive control of industrial processes using low level control hardware: A pilot-scale distillation column case study. Control Engineering Practice, 28, 34–48. doi:10.1016/j.conengprac.2014.02.016

Van der Ham, L. G. J., Van den Berg, H., Benneker, A., Simmelink, G., Timmer, J., Van Weerden, S. (2012). Hydrogenation of carbon dioxide for methanol production. Chemical Engineering Transactions, 29, 181–186. doi:10.3303/CET1229031

Wang, L. (2009). Model Predictive Control System Design and Implementation Using MATLAB. London: Springer, 378. doi:10.1007/978-1-84882-331-0

Skogestad, S. (1997). Dynamics and Control of Distillation Columns – A Critical Survey. Modeling, Identification and Control: A Norwegian Research Bulletin, 18 (3), 177–217. doi:10.4173/mic.1997.3.1

Skogestad, S. (2007). The Dos and Don’ts of Distillation Column Control. Chemical Engineering Research and Design, 85 (1), 13–23. doi:10.1205/cherd06133

Kothandaraman, J., Goeppert, A., Czaun, M., Olah, G. A., Prakash, G. K. S. (2016). Conversion of CO2from Air into Methanol Using a Polyamine and a Homogeneous Ruthenium Catalyst. Journal of the American Chemical Society, 138 (3), 778–781. doi:10.1021/jacs.5b12354

Drgona, J., Klauco, M., Valo, R., Bendzala, J., Fikar, M. (2015). Model identification and predictive control of a laboratory binary distillation column. 2015 20th International Conference on Process Control (PC), June 9-12, 2015, Strbske Pleso, Slovakia. Available: https://www.researchgate.net/publication/278392589_Model_Identification_and_Predictive_Control_of_a_Laboratory_Binary_Distillation_Column. doi:10.1109/pc.2015.7169989

Stopakevich, А. (2013). Sistemnyi analiz i teoriia slozhnyh sistem upravleniia. Оdessa: Astroprint, 380.


GOST Style Citations


Стопакевич, А. А. О возможности применения современных САПР химико-технологических систем для синтеза САУ нефтяными ректификационными колоннами [Текст] / А. А. Стопакевич, Н. И. Скакун // 4 Международная научно-практическая конференция «Экономика и управления в условиях построения информационного общества», Одесса, 27-29.04.2015. – Одесса: ОНАС, 2015. – С. 82–84.

Стопакевич, А. А. Синтез и исследование цифровых систем супервизорного управления колонной ректификации нефти [Текст] / А. А. Стопакевич, А. А. Стопакевич // Автоматизация технологических и бизнес процессов. – 2015. – № 4 (7). – С. 24–34.

Веремей, Е. И. Управление с прогнозирующими моделями [Текст] / Е. И. Веремей, М. В. Сотникова. – Санкт-Петербург: СПБГУ, 2014. – 212 с.

Huyck, B. Online model predictive control of industrial processes using low level control hardware: A pilot-scale distillation column case study [Text] / B. Huyck, J. De Brabanter, B. De Moor, J. F. Van Impe, F. Logist // Control Engineering Practice. – 2014. – Vol. 28. – P. 34–48. doi:10.1016/j.conengprac.2014.02.016

Van der Ham, L. G. J. Hydrogenation of carbon dioxide for methanol production [Text] / L. G. J. van der Ham, H. van den Berg, A. Benneker, G. Simmelink, J. Timmer, S. van Weerden // Chemical Engineering Transactions. – 2012. – Vol. 29. – P. 181–186. doi:10.3303/CET1229031

Wang, L. Model Predictive Control System Design and Implementation Using MATLAB [Text] / L. Wang. – London: Springer, 2009. – 378 p. doi:10.1007/978-1-84882-331-0

Skogestad, S. Dynamics and Control of Distillation Columns – A Critical Survey [Text] / S. Skogestad // Modeling, Identification and Control: A Norwegian Research Bulletin. – 1997. – Vol. 18, № 3. – P. 177–217. doi:10.4173/mic.1997.3.1

Skogestad, S. The Dos and Don’ts of Distillation Column Control [Text] / S. Skogestad // Chemical Engineering Research and Design. – 2007. – Vol. 85, № 1. – P. 13–23. doi:10.1205/cherd06133

Kothandaraman, J. Conversion of CO2from Air into Methanol Using a Polyamine and a Homogeneous Ruthenium Catalyst [Text] / J. Kothandaraman, A. Goeppert, M. Czaun, G. A. Olah, G. K. S. Prakash // Journal of the American Chemical Society. – 2016. – Vol. 138, № 3. – P. 778–781. doi:10.1021/jacs.5b12354

Drgona, J. Model identification and predictive control of a laboratory binary distillation column [Electronic resource] / J. Drgona, M. Klauco, R. Valo, J. Bendzala, M. Fikar // 2015 20th International Conference on Process Control (PC), June 9-12, 2015, Strbske Pleso, Slovakia. – Available at: \www/URL: https://www.researchgate.net/publication/278392589_Model_Identification_and_Predictive_Control_of_a_Laboratory_Binary_Distillation_Column. doi:10.1109/pc.2015.7169989

Стопакевич, А. А. Системный анализ и теория сложных систем управления [Текст] / А. А. Стопакевич. – Одесса: Астропринт, 2013. – 380 с.







Copyright (c) 2016 Виталий Семенович Пастушенко, Алексей Аркадьевич Стопакевич, Андрей Алексеевич Стопакевич

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

ISSN (print) 2664-9969, ISSN (on-line) 2706-5448