MPC as control strategy for pasta drying processes

Abstract

This study focuses on the drying process of pasta in a convectional air drying oven. A model predictive control algorithm is designed, based on a dynamic model describing the mass transfer between pasta and the surrounding air. The multiple input single output control algorithm minimizes a cost function over a prediction horizon which represents the deviation of the process from a desired reference track, thereby incorporating the working limitations of the oven. The performance of the controller and the influence of the prediction horizon are examined in this paper, showing minimal deviation between process and reference track.

Modeling and model predictive control of dividing wall column for separation of Benzene–Toluene-o-Xylene

“…The MPC offers a large number of operational advantages for diverse processes like reaction, separation, etc. (Backx, Bosgra, & Marquardt, 2000;De Temmerman, Dufour, Nicolaï, & Ramon, 2009). In view of the multi-input-multi-output system, the MPC is characterized by many manipulated and controlled variables and it may be performed for a complex system (Buck et al, 2011).…”

Predictive control with multiobjective optimization: Application to a sludge drying operation

“…The main objective is to follow an imposed temperature kinetic for the paint through determining the optimal command policy of the infrared emitter. Temmerman et al (2009) have proposed an optimization for a pasta drying process by using a predictive control strategy. The optimization is conducted with a single objective function related to the pursuit of a drying kinetic target.…”

Applying Model Predictive Control to Dividing Wall Columns

“…However, model predictive controllers offer a large number of operational advantages for diverse processes like reaction, separation, or drying units [11,12]. The controlled process is characterized by an enhanced performance and, thus, smaller settling times and oscillations in the case of disturbances.…”