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Dwi Saputra, Robi
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Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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Backpropagation neural network for DC-DC boost converter control using arduino microcontroller Dwi Saputra, Robi; Yuhendri, Muldi
Journal of Industrial Automation and Electrical Engineering Vol. 1 No. 1 (2024): Vol 1 No 1 (2024): June 2024
Publisher : Department of Electrical Engineering Universitas Negeri Padang

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Abstract

One kind of power converter that is frequently found in devices that employ a DC voltage source to produce a voltage output higher than the input voltage is the boost converter. The boost converter output voltage converter must be adjusted in order to produce the desired voltage output. This research suggests utilizing an Arduino Mega 2560 microcontroller implemented backpropagation-type artificial neural network to manage the boost converter output voltage. The highest output voltage of the boost converter is 24 volts, and its input voltage is 12 volts. Laboratory tests using different reference voltages and loads are used to validate the boost converter voltage control system based on a backpropagation neural network. Experiments conducted under a variety of test conditions demonstrate that the backpropagation neural network-based boost converter output voltage control system used in this study has effectively controlled the boost converter output voltage in accordance with the reference output voltage value, both when the load and the reference voltage are varied.
Co-Authors Muldi Yuhendri