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Nonlinear model predictive control for dividing wall columns |
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| Authors: | Xing Qian Kuan-Han Lin Shengkun Jia Lorenz T Biegler Kejin Huang |
| Affiliation: | 1. College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China;2. Chemical Engineering Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA
Contribution: Conceptualization (equal), Data curation (equal), Methodology (equal), Resources (equal), Software (equal);3. School of Chemical Engineering and Technology, Chemical Engineering Research Center, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), State Key Laboratory of Chemical Engineering, Tianjin University, Tianjin, China;4. Chemical Engineering Department, Carnegie Mellon University, Pittsburgh, Pennsylvania, USA;5. College of Information Science and Technology, Beijing University of Chemical Technology, Beijing, China Contribution: Funding acquisition (equal), Project administration (equal), Supervision (equal) |
| Abstract: | Dividing wall columns (DWCs) are practical, effective, and promising among distillation process intensification technologies. Nonlinear model predictive control (NMPC) schemes are developed in this study to control the three-product DWCs. As these systems are intensely interactive and highly nonlinear, NMPC may be more suitable than the traditional PI control. The model is established based on Python and Pyomo platforms. As the original mathematical model of the column section is ill-posed, index reduction is used to avoid a high-index differential-algebraic equation (DAE) system. The well-posed index-1 system after index reduction is employed for the steady-state simulation and dynamic control in this study. Case studies with three DWC configurations to separate the mixture of ethanol (A), n-propanol (B), and n-butanol (C) show that the NMPC performs very well with small maximum deviations and short settling times. This demonstrates that the NMPC is a feasible and very effective scheme to control three-product DWCs. |
| Keywords: | distillation dividing wall column nonlinear model predictive control |