Modeling and control of an electric heater in a pharmaceutical tablet coating machine

This thesis focuses on improving temperature regulation in an industrial pharmaceutical coating system by modeling and controlling its electric heater. A hybrid model, combining physics-based equations and data-driven components, is developed with the Least Squares method to accurately represent heater dynamics. An OPC-UA interface enables real-time data acquisition and external control, facilitating systematic controller design and evaluation. Two control strategies are proposed: a PID regulator employing back-calculation anti-windup with parameters tuned using the developed hybrid model, and a gain-scheduling controller designed to adapt across different operating points. Both strategies are first validated through simulation on the hybrid model, significantly reducing the effort required for experimental tuning. Subsequent experimental results, obtained from tests conducted on the actual machine, confirm that the proposed controllers achieve improved temperature regulation, demonstrated by reduced overshoot and shorter settling times compared to the existing industrial controller. The findings demonstrate the benefits of integrating model-based tuning into pharmaceutical coating processes, improving efficiency and accelerating the tuning phase. Additionally, they pave the way for more advanced model-based control strategies.