Model predictive control design of pressure swing distillation for methanol-c5 separation

The azeotropic mixture that is greatly influenced by pressure is usually separated by pressure-swing distillation (PSD). This paper investigates the control selection of the PSD system. The PSD scheme was developed by Luyben. Model predictive control (MPC) is used as an alternative control method because it had a better response compared to the proportional-integral (PI) controller. MPC utilizes a dynamic model to make a control action toward the process. Generating the model is a crucial step for the MPC to work accurately. In this work, the model representing the process was approached by the first order plus dead time (FOPDT) model. The steady-state and dynamic simulations were carried out with HYSYS V11. The fine-tuning method was used to find the optimum tuning parameter of MPC meanwhile, the PI controller was tuned by auto-tuner. The results show that MPC was successfully implemented to the process and the control performance has increased by 21-52% in the set-point tracking test and 5-42% in disturbance rejection test compared to the PI controller.