A review of artificial intelligence based control techniques for power electronics

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.