Online learning artificial neural network controller for a buck converter

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8 Citas (Scopus)

Resumen

This paper presents an Online Learning Artificial Neural Network Controller (OLANNC) for a DC-DC Buck converter. The proposed control scheme uses a Perceptron Online Learning algorithm to stabilize the output voltage. The OLANNC obtains the appropriate duty cycle of the PWM signal that determines the switching operation of the semiconductor device. To verify the effectiveness of the proposed method, a simulation results are presented with some operations such as reference voltage variations. Comparison with a typical controller is also presented to denote it advantages.

Idioma originalInglés
Título de la publicación alojada2019 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2019
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781728128986
DOI
EstadoPublicada - nov. 2019
Evento2019 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2019 - Ixtapa, Guerrero, México
Duración: 13 nov. 201915 nov. 2019

Serie de la publicación

Nombre2019 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2019

Conferencia

Conferencia2019 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2019
País/TerritorioMéxico
CiudadIxtapa, Guerrero
Período13/11/1915/11/19

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