Model identification for crystallization: Theory and experimental verification

This paper presents model identification and open-loop optimal control strategies for batch cooling crystallizers. The techniques are evaluated with experimental data from two chemical systems,:KNO3-H2O and an organic photochemical-heptane system. The model identification scheme is a maximum likelihood method that includes a linearized assessment of parameter uncertainty. The connection between this uncertainty and the optimal open-loop control profiles for the two systems is examined. The control scheme handles input, output, and final-time constraints and is applicable to crystallization with size-dependent growth rate, growth dispersion, and fines dissolution. The objective function can be formulated to take into account solid-liquid separation in subsequent processing steps.