Model Identification and Control Strategies for Batch Cooling Crystallizers

The study of an optimal cooling control strategy for a batch white sugar crystallization process is reported in this paper. Within the proposed control strategy, a dynamic optimization algorithm (DOA) and a generic model control (GMC) algorithm were compared with respect to the final process quality achieved. The linear models required in the controller structures were extracted applying two identification alternatives. The GMC algorithm cases seem to guarantee more satisfactory end point quality of the process. However, only the DOA of the supersaturation manipulating the steam flowrate makes feasible all conflicting control objectives.