Control of the Moisture Content of Milk Powder Produced in a Spouted Bed Dryer Using a Grey-Box Inferential Controller

Abstract

Although the moisture content of dried products is an important variable in industrial dryers, it is often not measured directly for control purposes. Alternative and simpler meters might provide information to be used in a physical-mathematical model to estimate the moisture content. When this procedure is applied to a control strategy, an inferential controller is developed. In this article, a physical-mathematical model was used to infer the moisture content of milk powder produced in a spouted bed dryer. Afterwards, simulations of an inferential proportional-integral controller were carried out using the inlet air heating rate as the manipulated variable. The physical-mathematical model used in the procedure was a hybrid model, which considers mass and energy balances and one term which is estimated by an artificial neural network. The controller parameters (controller gain and integral time) were tuned by trial and error. Even though the procedure was quite simple, it was proven to be effective in yielding a stable closed-loop response for both servo and regulatory control of the (inferred) powder moisture content.

Keywords:

• Artificial neural network
• Food drying
• Mathematical modeling
• Spouted bed drying