Integrating a dynamic multiscale drying model into a closed loop control strategy for laboratory spray dryer

Abstract

Spray drying is a widely used unit operation in synthesis of particles for production of chemicals, food, and pharmaceuticals. However, accurate control and development of this unit remains an elusive task because of the complex interactions of variables and phenomena. In this paper, we adopt and present a dynamic model of the complete drying process for a laboratory spray dryer. The dynamic mathematical model, which integrates atomization, evaporation, and particle formation models, is described by mass and energy balances. The model can predict temperature, residual moisture, and particle size of the produced powder. Model predictions are verified through datasets collected from a lab-scale spray dryer. A data-driven model based on the dynamic model is produced to interface with the control strategy. A model predictive control (MPC) strategy is then adopted to address the highly cross-coupled effects among different components of the dryer and guarantee desired product quality measures. Successful MPC implementation on the drying system is addressed, including trajectory tracking and disturbance rejection scenarios.

Keywords:

• Spray drying
• model predictive control
• drying kinetics
• particle engineering
• process control

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This study was funded by the DoD Grant entitled “Acquisition of a Lab-Scale Spray Dryer and a Particle Size Analyzer for the Improvement of Undergraduate and Graduate Research and Education Capabilities at Tuskegee University"; with grant number of W911NF1910508.