Dynamic Model for the pH in a Raceway Reactor Using Deep Learning Techniques

Abstract

This paper presents a black-box dynamic model for microalgae production in raceway reactors. The black-box model, developed using Deep Learning techniques, allows the estimation of the pH in a 100 m\(^2\) raceway reactor. The model has been created using only and exclusively data, what gives a high ease of use. The results obtained verify the effectiveness of this type of techniques for the modelling of complex dynamic processes. The model was validated for different weather conditions obtaining satisfactory results. Thus, the obtained model is fairly useful for simulation purposes or for the implementation of model-based control techniques.