Model Predictive Control of a High‐Purity Internal Thermally Coupled Distillation Column

• Published in: Chemical engineering & technology Vol. 44; no. 7; pp. 1294 - 1301
• Main Authors: Zangina, Ja'afar Sulaiman, Wang, Wenhai, Qin, Weizhong, Gui, Weihua, Zhang, Zeyin, Xu, Shenghu, Yang, Chunhua, Wang, Yalin, Liu, Xinggao
• Format: Journal Article
• Language: English
• Published: Frankfurt Wiley Subscription Services, Inc 01.07.2021
• Subjects: Adaptive control; Air separation; Air separation columns; Direct finite‐horizon control; Distillation; Dynamic characteristics; Energy saving; Model predictive control; Multivariable control; Predictive control; Purity
• ISSN: 0930-7516; 1521-4125
• DOI: 10.1002/ceat.202000617

The energy‐saving potential of the internal thermally coupled air separation column (ITCASC) is well‐established, but distinct dynamic characteristics and control loop interactions make it inflexible to control. To take care of high‐purity ITCASC control complications, a state‐space model predictive control (MPC) was formulated. A direct finite‐horizon control approach was exploited to align the dynamic states with the model predictions. MPC‐I and MPC‐II were developed, and further compared to a previous adaptive multivariable generalized prediction control (AM‐GPC). The results obtained show that the control performance of the proposed MPC‐II is superior to that of MPC‐I and AM‐GPC. The internal thermally coupled air separation column is an advanced energy‐saving technology for producing nitrogen, argon, and oxygen, but its dynamic characteristics and control loop interactions make it inflexible to control. Hence, a state‐space model predictive control was formulated, and a direct finite‐horizon control approach was used to align the dynamic states with the model predictions.