Skip to content
Licensed Unlicensed Requires Authentication Published by De Gruyter September 18, 2019

Change in Distillation Column Control Philosophy Using Dynamic Simulation

Kanubhai Parmar ORCID logo, Sukanta Dash, Sunil Patil and Garimella Padmavathi


At condensate stripper of a cracker plant with design control philosophy for composition control pant was facing operational difficulty. Due to disturbance in operating parameter column was becoming unstable and product was getting offspec w.r.t. desired purity. One of the applications of dynamic simulation is to troubleshoot the challenges related to control philosophy in practical application. Since steady-state simulation models cannot predict behavior with respect to time, initially steady state model and finally a dynamic model was developed in Aspen HYSYS. The model is used to study the process behavior for existing control philosophy and proposed philosophy. To avoid column puncture and without waiting for plant shut down the existing Temperature Indicator (TI) considered as Temperature Indicator Controller (TIC) for the study. A new control philosophy was developed based on the response of variables after disturbances in feed rate and composition. The revised control philosophy has been implemented and is now working satisfactorily, providing stabilized operation of the column with consistent bottom product quality. This has helped to reduce the loss of C2s in the bottom stream by about 700 ppm, for savings of about $100,000 USD per year.


[1] Skogestad S. The dos and don’ts of distillation column control. Trans IChemE. 2007;85:13–23. DOI: 10.1205/cherd06133.Search in Google Scholar

[2] Hori ES, Skogestad S. 2006. Self-optimizing control configurations for two-product distillation column. Special issue of Chemical Engineering Research and Design from Distillation and Absorption Symposium. London. /publications/2006/hori_distillation06/hori_paper056.pdf.Search in Google Scholar

[3] Luyben WL. Guides for the selection of control structure for ternary distillation column. Ind Eng Chem Res. 2005;44:7113–19. DOI: 10.1021/ie058015z.Search in Google Scholar

[4] Luyben WL. Control of train of distillation column for the separation of natural gas. Ind Eng Chem Res. 2013;10741–53. DOI: 10.1021/ie400869v.Search in Google Scholar

[5] Firmino CK, DA Silva AC, DA Silva MM, Biaggi PN, Ferreira NL. Dynamic simulation of an industrial distillation column. J Eng Exact Sci. 2019;15:143–7. DOI: 10.18540/jcecv15issu1pp0143-0147.Search in Google Scholar

[6] Rademaker O, Rijnsdorp JE, Maarleveld A. Dynamics and control of continuous distillation units. Amsterdam, 1976. DOI: 10.1002/aic.690220633.Search in Google Scholar

[7] Ziyan W, Zhang J, Xu Q, Ho TC. 2014. Dynamic simulation for optimal operation of distillation column startups in an ethylene plant. Proceedings of the 26th Ethylene Producers’ Conference. New Orleans. in Google Scholar

[8] Eluge S, Prata L, Cabassuda M, Le Lanna JM, Cezerac J. Dynamic models for start-up operations of batch distillation columns with experimental validation.Search in Google Scholar

[9] Elakkiya T, Priyanka R, Kiruthika S and Padma Priya R. Comparative study of PID, IMC and IMC based PID controller for pressure. J Chemi Pharm Sci 2015;10:32–39. in Google Scholar

Received: 2019-07-31
Revised: 2019-08-30
Accepted: 2019-09-01
Published Online: 2019-09-18

© 2019 Walter de Gruyter GmbH, Berlin/Boston