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Implementation of Small-Scale Artificial Neural Networks for Power Electronics Applications
Date
2025-01-01
Author
Alemdar, Ozturk Sahin
Keysan, Ozan
Metadata
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Artificial Neural Networks (ANNs) can be used in power converter applications to identify a relationship between the input variables and target output variables dependent on these input variables. This feature can be used to integrate enhanced control capabilities into power converters. ANNs can be deployed in digital controllers running on power converters for real-time tasks. In such applications, the memory and computation requirements of the implemented ANN model become critical. In this study, different feed-forward ANN models are first implemented. Then, their inference durations and memory sizes are compared. Optimal phase-shift angle prediction using ANNs for PWM interleaving in multi-input single-output power converters is also addressed as a case study.
URI
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105013850633&origin=inward
https://hdl.handle.net/11511/115749
DOI
https://doi.org/10.30420/566541291
Conference Name
2025 International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Europe 2025
Collections
Department of Electrical and Electronics Engineering, Conference / Seminar
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BibTeX
O. S. Alemdar and O. Keysan, “Implementation of Small-Scale Artificial Neural Networks for Power Electronics Applications,” presented at the 2025 International Exhibition and Conference for Power Electronics, Intelligent Motion, Renewable Energy and Energy Management, PCIM Europe 2025, Nuremberg, Almanya, 2025, Accessed: 00, 2025. [Online]. Available: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=105013850633&origin=inward.