Predictive controller with estimation of measurable disturbances. Application to an olive oil mill

This paper describes the application of a predictive controller that deals with measurable disturbances in the extraction process in an olive oil mill. The work focuses on the thermal part of the process, where the raw material is prepared for the mechanical separation. The system under consideration can be viewed as composed of several changing-level stirred tanks. The paper shows the development of the controller based upon a model obtained from first principles combined with experimental results and validated with real data. Strong disturbances and large time delays appear in the process, so predictive control strategies have been tested under linear and nonlinear simulation. Finally, they have been implemented on the real plant. A study about the consideration of different models for the estimation of measurable disturbances along the prediction horizon has been carried out, showing that a good performance can be obtained by the use of an appropriate model. A new idea that can improve periodic disturbance rejection in Model Based Predictive controllers is presented.