Model Predictive Control Based on System Re-Identification for Methanol and Dimethyl Ether Synthesis Control

Abstract

To improve the performance of the model predictive control (MPC) was carried out by improving the model used. In this study the improvement was carried out by a closed loop system re-identification. In addition, the MPC tuning was carried also to obtain a more optimum control performance. The MPC based on a system re-identification (MPC-SRI) was used to control the synthesis of methanol and dimethyl ether, and compared with the PI controller. The results provide better performance than PI controller by decreasing the errors for each unit as follows:  29,62% (IAE) and 1,51% (ISE) for TC (temperature control) Heater 1; 51,69% (IAE) and 79,04% (ISE) for TC Heater 2; 67,44% (IAE) and 82,24% (ISE) for TC Cooler 1; 49,07% (IAE) and 67,26% (ISE) for TC Cooler 2; 56,75% (IAE) and 53,03% (ISE) for PC (pressure control) Compressor; 4,46% (IAE) and 50,00% (ISE) for CC (composition control) DME.