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

被引：0

作者：

Yair Bote-Vazquez, Marcos ^{[1
]}

Ramirez-Hernandez, Jazmin ^{[1
]}

Hernandez-Gonzalez, Leobardo ^{[1
]}

David Delgado-Pina, Eric ^{[1
]}

Ulises Juarez-Sandoval, Oswaldo ^{[1
]}

机构：

[1] Inst Politecn Nacl, ESIME Culhuacan, Ciudad De Mexico, Mexico

来源：

2022 IEEE INTERNATIONAL AUTUMN MEETING ON POWER, ELECTRONICS AND COMPUTING (ROPEC) | 2022年

关键词：

Artificial Neural Network; Buck converter; Predictive Control; Voltage regulation;

D O I：

10.1109/ROPEC55836.2022.10018649

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

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.

引用

页数：6

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