Abstract
This paper presents the application of certain intelligent techniques to control an industrial mixer. Control design is based on Hebbian modification of Fuzzy Cognitive Maps learning. This research study develops a Dynamic Fuzzy Cognitive Map (DFCM) based on Hebbian Learning algorithms. It was used Fuzzy Classic Controller to help validate simulation results of an industrial mixer of DFCM. Experimental analysis of simulations in this control problem was conducted. Additionally, the results were embedded using efficient algorithms into the Arduino platform in order to acknowledge the performance of the codes reported in this paper.
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Mendonça, M., Neves, F., de Arruda, L.V.R., Chrun, I.R., Papageorgiou, E.I. (2016). Embedded Dynamic Fuzzy Cognitive Maps for Controller in Industrial Mixer. In: Czarnowski, I., Caballero, A.M., Howlett, R.J., Jain, L.C. (eds) Intelligent Decision Technologies 2016. Smart Innovation, Systems and Technologies, vol 57. Springer, Cham. https://doi.org/10.1007/978-3-319-39627-9_22
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DOI: https://doi.org/10.1007/978-3-319-39627-9_22
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