A review of artificial intelligence based control techniques for power electronics | ||
| Journal of Artificial Intelligence in Engineering Practice | ||
| Volume 2, Issue 2, November 2025, Pages 37-50 PDF (780.42 K) | ||
| Document Type: Original Article | ||
| DOI: 10.21608/jaiep.2025.416768.1021 | ||
| Authors | ||
| Ahmed Abdelhaleim* 1, 2; Ahmed Shahin3; Mostafa Al-Gabalawy4; Akram Elmitwally3 | ||
| 1Department of Communication Techniques Engineering, Al-Farahidi University, Baghdad, 10021, Iraq | ||
| 2Electrical Engineering Department, Faculty of Engineering, Mansoura University, 43512, Egypt | ||
| 3Electrical Engineering Department, Faculty of Engineering, Mansoura University, 35516, Egypt | ||
| 4Electrical Engineering Department, Faculty of Engineering, Suez University, 43512, Egypt | ||
| Abstract | ||
| The integration of Artificial Intelligence (AI) into power electronics marks a major advancement in control techniques, providing increased efficiency, adaptability, and reliability across various industrial and commercial applications. This research paper aims to present and review the fields of AI in control systems, focusing on key AI-based techniques such as neural networks, fuzzy logic, genetic algorithms, and reinforcement learning, and their use in power converters, renewable energy systems, electric drives, and smart grids. Through case studies, it demonstrates the practical benefits of these techniques in optimizing performance. While the advantages are significant, the paper also examines the technical challenges, ethical concerns, and societal implications related to AI adoption in power electronics. Future trends, including the development of hybrid AI techniques and the need for explainable AI models, are discussed to ensure transparency and accountability. Although AI is set to revolutionize power electronics, overcoming existing challenges is crucial for its full potential to be realized. | ||
| Keywords | ||
| Artificial intelligence; control techniques; power electronics; renewable energy systems; smart grids | ||
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