Quantum Power Electronics: From Theory to Implementation
نویسندگان
چکیده
While impressive progress has been already achieved in wide-bandgap (WBG) semiconductors such as 4H-SiC and GaN technologies, the lack of intelligent methodologies to control gate drivers prevented exploitation maximum potential semiconductor chips from obtaining desired device operations. Thus, a potent ongoing trend is design fast driver switching scheme upgrade performance electronic equipment at system level. To address this issue, work proposed novel for using concept quantum computation machine learning. In particular, principle was incorporated into deep reinforcement learning (DRL) hardware limitations conventional computers growing amount data sets. Taking benefit theory, DRL algorithm influenced by specifications (referred QDRL) not only ameliorates native on traditional but also enhances relevant research fields like computing test practicability usefulness QDRL, dc/dc parallel boost converter feeding constant power loads (CPLs) chosen case study, several hardware-in-the-loop (PHiL) experiments comparative analysis were performed.
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ژورنال
عنوان ژورنال: Inventions
سال: 2023
ISSN: ['2411-5134']
DOI: https://doi.org/10.3390/inventions8030072