Model-Based Evaluation of Direct Nucleation Control Approaches for the Continuous Cooling Crystallization of Paracetamol in a Mixed Suspension Mixed Product Removal System

Direct nucleation control (DNC) is a model-free feedback control approach based on the measurement of particle number in the crystallization process. The experimental implementation has demonstrated that this approach is efficient to produce large and uniform crystals in batch crystallization, or to reduce startup duration and suppress disturbance in continuous crystallization. In this work, five different DNC frameworks/strategies are proposed for a continuous mixed suspension mixed product removal (MSMPR) crystallization of paracetamol water system and evaluated systematically using a model based approach. It is found that the reverse DNC framework could provide the best control performance in terms of startup, set-point change, and disturbance suppression. In addition, an optimal heating/cooling rate of about 0.6 degrees C/min was determined. These observations are applicable for the model compound studied (paracetamol) and should be investigated for other systems. This study provides a general guidance of designing a DNC framework with the best control performance for continuous MSMPR crystallization.