Model predictive control for continuous pharmaceutical manufacturing with mass retention constraints

Abstract

The pharmaceutical industry is undergoing a significant shift from batch to continuous production processes in pursuit of enhanced productivity and profitability. This motivates the research of control techniques for continuous pharmaceutical manufacturing. Unlike batch processing, continuous pharmaceutical manufacturing involves a single input of raw materials, with all subsequent steps operating in an uninterrupted flow. This paper presents the application of constrained model predictive control (MPC) for the feeding and mixing units in continuous pharmaceutical manufacturing with mass retention constraints. Based on mechanistic modeling, we develop a dynamic model of the continuous pharmaceutical process by introducing two integral state variables, which allow to characterize mass retention constraints. With this model, we then design a MPC scheme to track the desired outlet mass flow subject to mass retention constraints. Finally, the effectiveness of the proposed MPC scheme is validated by a simulation example.