This paper presents the application of intelligent techniques to control an industrial mixer. Control design is based on hebbian evolution of fuzzy cognitive maps. In this context, this paper develops a dynamical fuzzy cognitive map (D-FCM) based on Hebbian Learning algorithms. Two strategies to update FCM weights are derived. Finally, the D-FCM is used to control an industrial mixer. Simulation results of this control are presented. Additionally, results are provided extending some of the algorithms into the Arduino platform in order to acknowledge the performance of the codes reported in this paper.