MODEL-FREE CONTROL OF A SEEDED BATCH CRYSTALLIZER

As the use of a batch crystallization process in several industrial applications is extensive, finding an effective control strategy is important to improve the product quality, which is typically characterized by a unimodal and narrow crystal size distribution (CSD) with a large mean crystal size. To achieve this requirement, an accurate mathematical model is needed to predict the process comportment and to design an efficient and robust controller. However, due to the highly nonlinear comportment, the difficulties of characterizing several phenomenological effects, the kinetic parameters, uncertainty, and the unknown disturbances, the used model may not describe the real process behaviour, resulting in a poor control strategy. In this work, a model-free control and its corresponding intelligent PI (iPI), the recently introduced approach, has been proposed to ensure that the desired unimodal CSD with a desired mean size could be reached facing these problems with an easy control structure, choosing the seeded batch crystallizer of adipic acid as a case study. The proposed iPI is compared with the classic PI controller. The simulation results demonstrate the effectiveness and disturbance rejection capability of the iPI controller against the classic PI.