Estimation of the IDGREY model and by adaptive interaction applied to an EMG30 dc motor
DOI:
https://doi.org/10.18687/LACCEI2023.1.1.1231Palabras clave:
Parameter identification, speed control, DC motor, adaptive controller.Resumen
This research carried out the development of the experimental model through the acquisition of data from a direct current motor, through the identification of a gray box model for speed control under the LabVIEW platform. The precision of the experimental model was validated by solving the speed control problem of the DC motor, in this case the adaptive interaction control technique was applied to a multilayer perceptron network, obtaining as a result an error prediction of 97%. With which it is concluded that the system adapts quite well to the precision of the model.
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2023-07-27
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Derechos de autor 2023 LACCEI
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Esta obra está bajo una Licencia Creative Commons Atribución-NoComercial-CompartirIgual 4.0 Internacional.
LACCEI conserva el copyright de todos los artículos publicados bajo los términos de su acuerdo de transferencia de copyright. Como titular del copyright, LACCEI distribuye los artículos al público bajo la Licencia Internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0 (CC BY-NC-SA 4.0).
Cómo citar
Rodriguez-Bustinza, Ricardo, Rubiños-Jimenez, Santiago, Mendoza-Nolorbe, Juan, Santos-Mejia, Cesar, Mendoza-Apaza, Fernando, Leva-Apaza, Antenor, & Tejada-Cabanillas, Adan. (2023). Estimation of the IDGREY model and by adaptive interaction applied to an EMG30 dc motor. LACCEI, 1(8). https://doi.org/10.18687/LACCEI2023.1.1.1231