Integrating Dynamic Composition Estimation with Model Based Control for Ethyl Acetate Production

Abstract

To achieve a high purity of the ethyl acetate production in the batch reactive distillation, an optimal operating condition and an effective control strategy are needed to improve the product quality (maximum of the high purity product). An off-line dynamic optimization is prior determined by maximizing productivity for the batch reactive distillation. A dynamic composition estimation (EKF) based on simplified mathematical models and on-line temperature measurements, is incorporated to estimate the compositions in the reflux drum and the reboiler. The estimate performances of the EKF are investigated the influence of changing in the initial compositions. Model based control, model predictive control (MPC), has been implemented to provide tracking of the desired product compositions subject to rigorous model equations. Simulation results demonstrate that the EKF can still provide good estimates of compositions in the reflux drum and reboiler with respect to the initial compositions change. The MPC based on rigorous mathematical models with the dynamic composition estimator can control the distillation according to the optimal trajectory and then can achieve maximum product as determined. In the presence of the forward reaction rate constant mismatch (unknown/uncertain parameters case), the EKF is still able to provide good accuracy. The MPC integrating with dynamic composition estimation is robust and able to handle the mismatch.