Analysis and control of a turbulent coagulator

Recent developments of particle sizing sensors and control algorithms together with a better understanding of the physics of coagulation processes foster the application of advanced control systems to aggregating particulate systems in order to ensure the product quality despite disturbances and model errors. A model containing the main features of coagulation dynamics in shear flows, including aggregation, breakage, and time evolution of the cluster fractal dimension, was introduced and tuned to reproduce experimental data from the literature. Using this model, a set of particulate products, in terms of the mean size and fractal dimension, that can be obtained with different shear rate policies was identified. Finally, a control algorithm, the batch model predictive control, was applied to the system. The algorithm exploits the fact that batch processes are run repetitively and the availability of online measurements. The controller, tested with simulations, was able to guarantee the product quality in terms of the mean radius of gyration by adjusting the shear rate according to the current measurements and the results obtained in previous batches.