Model identification and control of batch crystallization for an industrial chemical system

The final-time crystal size distribution (CSD) of a batch crystallization slurry affects the efficiency of solid-liquid separation processes such as filtration and drying. This study examines the improvement of slurry filtration through the determination of optimal temperature profiles for seeded, batch cooling crystallizers. The temperature profiles are optimized subject to a fundamental model of the dynamics of the CSD. The model is identified for a photochemical produced by the Eastman Kodak Company. This crystallization exhibits some problems common to industrial crystallizations including irregular crystal habit and poorly characterized CSD.;Using a population balance structure, this study identifies the kinetic models describing crystal nucleation and growth of the photochemical system. The kinetic parameters are inferred from on-line measurements of liquid phase solute concentration and slurry turbidity using Bayesian estimation methods. A novel model is identified to account for crystal habit dynamics. Linear 95% confidence intervals evaluate the uncertainty in the parameter estimates. Two of the identification experiments are designed to minimize parameter uncertainty using optimal experimental design techniques.;The filtration of a crystallization slurry is facilitated when the particles are large and the size variance of the population is small. This study focuses on the filtration benefits of minimizing the final-time mass of nucleated crystals relative to the mass of seed crystals. A nonlinear program minimizes the objective function with respect to the batch temperature profile, subject to final-time and path constraints. The sensitivity of the optimal temperature profile to seed mass, run duration, and parameter uncertainty are analyzed.;Improvements in filtration resulting from implementation of two optimized input profiles are quantified experimentally by calculation of the average specific cake resistance. The filtration results for the optimal experiments are compared to those from the model identification experiments. The optimized slurries give the lowest resistance values recorded during the study and the filtration times for the controlled runs are shorter despite higher solids densities. The best optimal profile gives a cake resistance 25% lower than the best identification experiment.