(440e) Optimization of a Fluid Bed Dryer by the Implemention of a Model Predictive Controller

Drying is essential for industries such as pharmaceutical and food; however modeling of fluid bed dryers (FBD), one of the technologies most used for this purpose, is still uncertain. Furthermore, the optimization of this operation requires a model containing the operating variables. The objective of this research was to develop a first principle model that would describe the moisture content of a pharmaceutical powder as a function of operating variables and to use it for optimization purpose. Granulations consisting of lactose monohydrate and pregelatinized starch combined with distilled water were dried in a FBD to generate the data to develop the models. Using basic energy and material balance we can describe the drying curve and use the model to determine the parameters necessary to design a customized MPC controller. The simulation shows that by implementing an MPC controller we get to the desired set point in half the time as to working at the fluid bed dryer’s maximum settings, plus consuming less energy. Compared to traditional MPC strategy, this customized controller provided a more logical response of the drying process since the traditional MPC strategy is more accurate when it is applied to a stable process. Compared to a PID strategy, the MPC proved to be a better tool for optimizing the drying process since the response of the PID was the equivalent of not implementing any control strategy.