Intelligent Systems Applied to the Control of an Industrial Mixer

Abstract : 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.
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Communication dans un congrès
Harris Papadopoulos; Andreas S. Andreou; Lazaros Iliadis; Ilias Maglogiannis. 9th Artificial Intelligence Applications and Innovations (AIAI), Sep 2013, Paphos, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-412, pp.537-546, 2013, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-41142-7_54〉
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Marcio Mendonça, Douglas Matsumoto, Lucia Arruda, Elpinik Papageorgiou. Intelligent Systems Applied to the Control of an Industrial Mixer. Harris Papadopoulos; Andreas S. Andreou; Lazaros Iliadis; Ilias Maglogiannis. 9th Artificial Intelligence Applications and Innovations (AIAI), Sep 2013, Paphos, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-412, pp.537-546, 2013, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-642-41142-7_54〉. 〈hal-01459645〉

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