Desarrollo de un controlador neuro difuso sobre un sistema embebido y monitoreo remoto de variables a través de una plataforma iot. aplicación al control de velocidad de un motor de corriente directa

Abstract

This article describes the development and application of a real-time neuro fuzzy controller to control the speed of a direct current motor. To tune the fuzzy neuro control, training was applied using an artificial neural network tuned with a fuzzy algorithm using LabVIEW and Matlab as the programming environment, as well as an embedded system myRio-NI. The platform used for monitoring the engine variables is Ubidots with communication through hypertext transfer protocols (http). An engine model was identified in Matlab with open loop analysis. The neuro fuzzy system was trained from a PID controller to obtain a better stabilization of the motor having a following error in the trajectory with an error of a range of +/- 1 rpm of the full scale.