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ThinkMind // International Journal On Advances in Systems and Measurements, volume 10, numbers 3 and 4, 2017 // View article sysmea_v10_n34_2017_13


Dynamic Fuzzy Cognitive Maps Embedded and Intelligent Controllers Applied in Industrial Mixer Process

Authors:
Lucas Botoni de Souza
Patrick Prieto Soares Soares
Ruan Victor Pelloso Duarte Barros Barros
Marcio Mendonça Mendonça
Elpiniki I. Papageorgiou Papageorgiou

Keywords: Cognitive Maps; Hebbian Learning; Arduino Microcontroller; Process Control; Fuzzy Logic; Artificial Neural Network

Abstract:
This paper presents the application of certain intelligent techniques to control an industrial mixer. The controller design is based on a Hebbian modification of the Fuzzy Cognitive Maps learning mechanism. This research develops a Dynamic Fuzzy Cognitive Map (DFCM) based on Hebbian Learning algorithms. Fuzzy Classic Controller was used to help validate simulation results of an industrial mixer controlled by DFCM. Experimental analysis of simulations in this control problem was conducted. Additionally, the results were embedded using efficient algorithms into the Arduino platform to acknowledge the performance of the codes reported in this paper.

Pages: 222 to 233

Copyright: Copyright (c) to authors, 2017. Used with permission.

Publication date: December 31, 2017

Published in: journal

ISSN: 1942-261x

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