Artificial Neural Network-Based Voltage Control in a DC-DC Converter using a Predictive Model

Marcos Yair Bote-Vazquez, Jazmin Ramirez-Hernandez, Leobardo Hernandez-Gonzalez, Eric David Delgado-Pina, Oswaldo Ulises Juarez-Sandoval

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

3 Citas (Scopus)

Resumen

This paper proposes an ANN-based controller in a DC-DC converter to regulate the output voltage. The learning process to determine the optimal switching conditions in the converter is implemented by using a data set of model predictive control operation. This process is developed in Matlab-Simulink and once the ANN is fine-tuned, it is implemented in a microcontroller to regulate the output voltage in a Buck converter prototype. The proposed control algorithm is simple and also reduces the computational cost in the final implementation.

Idioma originalInglés
Título de la publicación alojada2022 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2022
EditorialInstitute of Electrical and Electronics Engineers Inc.
ISBN (versión digital)9781665458924
DOI
EstadoPublicada - 2022
Evento2022 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2022 - Ixtapa, México
Duración: 9 nov. 202211 nov. 2022

Serie de la publicación

Nombre2022 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2022

Conferencia

Conferencia2022 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2022
País/TerritorioMéxico
CiudadIxtapa
Período9/11/2211/11/22

Huella

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