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Integrating a dynamic multiscale drying model into a closed loop control strategy for laboratory spray dryer
Drying Technology ( IF 3.3 ) Pub Date : 2021-07-08 , DOI: 10.1080/07373937.2021.1934692
Sadegh Poozesh 1 , Christian A. Cousin 2
Affiliation  

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.



中文翻译:

将动态多尺度干燥模型集成到实验室喷雾干燥器的闭环控制策略中

摘要

喷雾干燥是用于生产化学品、食品和药品的颗粒合成中广泛使用的单元操作。然而,由于变量和现象的复杂相互作用,该单元的准确控制和开发仍然是一项难以捉摸的任务。在本文中,我们采用并提出了实验室喷雾干燥器完整干燥过程的动态模型。动态数学模型集成了雾化、蒸发和粒子形成模型,由质量和能量平衡描述。该模型可以预测所生产粉末的温度、残留水分和粒度。通过从实验室规模的喷雾干燥器收集的数据集验证模型预测。生成基于动态模型的数据驱动模型以与控制策略交互。然后采用模型预测控制 (MPC) 策略来解决干燥机不同组件之间的高度交叉耦合效应,并保证所需的产品质量措施。解决了干燥系统上成功的 MPC 实施,包括轨迹跟踪和干扰抑制场景。

更新日期:2021-07-08
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