Dynamic mode decomposition based MPC of fluidized bed spray agglomeration

Fluidized bed spray agglomeration (FBSA) is an efficient particle formation process for the production of granules extensively used in the food, agricultural and pharmaceutical industry. Specifications on agglomerate properties such as the agglomerate size determine the quality of the product and can be controlled by varying different process conditions. In this contribution data-driven model predictive control (MPC) of the average agglomerate size is presented. Dynamic mode decomposition (DMD) is used to identify a linear model of the process dynamics from snapshot measurements of the particle size distribution. Using DMD as system identification technique eliminates the complex process of identifying a mechanistic process model and at the same time includes advantageous model order reduction for the MPC application. The DMD model is obtained from simulated data and validated against a second, independent, data set. Subsequently, the model is deployed in an MPC controller, which is tested in a simulation study, showing promising performance in set point tracking and disturbance rejection scenarios.