Abstract
This study presents a novel approach for the implementation of a real-time dynamic optimal control methodology on a seeded, anti-solvent batch crystallization process. The novel features of the approach include online estimation of the nucleation, growth rates and moments of paracetamol in isopropanol–water solution using the FBRM ® probe, and the real-time single and multi-objective optimization. In addition, the supersaturation was measured by ATR-FTIR spectroscopy. The crystallization model, which involved population and mass balance, was solved based on the finite difference method. The results of the multi-objective optimization showed a substantial improvement of the end of batch properties expressed in terms of the volume-weighted mean size and yield. The effect of mean size of seeds was studied as well, and it was found that the seeds with smaller mean volume-weighted mean size promoted the growth rate. The multi-objective optimal control resulted in an increase in the volume-weighted mean size by 120.8 μ m compared to the seeds and 51% of theoretical yield, which showed better performance compared to other optimal control policies.
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