A modified method for modelling, optimization and control of an anti-solvent crystallization process

Abstract

Crystallization is a complex process of heat and mass transfer, its product quality is affected by many factors, thus it is a challenge to control this process. Modelling and optimization of the manipulated variables is a feasible way to improve the product quality of crystallization. In this paper, a modified numerical scheme is developed to solve the process model of anti-solvent batch crystallization. The proposed numerical scheme can handle growth, nucleation, agglomeration and breakage kinetics by means of the Method of Characteristics (MOC), which provides an accurate and efficient result of the crystal size distribution (CSD). Then Non-linear Model Predictive Control (NMPC) and non-linear Moving Horizon Estimation (MHE) are presented to provide a temperature profile for optimizing the CSD. The result of case studies indicates that the calculated results of the MOC modified process model were in agreement with the experimental results, which indicated that the MOC method could deal with the specific crystallization process efficiently and accurately. The NMPC-MHE optimized temperature control strategy was tested using the verification experiment of anti-solvent crystallization of β-Artemether, the validated result indicated that the method developed had high feasibility and accuracy. The computational time for the MHE and NMPC formulations with 90 control and sampling steps is well within the sampling interval, which allows for real time process control.