AI-Based Adaptive Control Systems for Power Electronics

Abstract

Power electronics play a crucial role in modern electrical systems, facilitating efficient energy conversion, distribution, and management. Traditional control techniques have been widely employed to regulate power electronic systems, but they often face challenges in handling nonlinearities, uncertainties, and dynamic operating conditions effectively. In recent years, there has been growing interest in harnessing artificial intelligence (AI) techniques to develop adaptive control systems for power electronics. These AI-based systems offer the capability to dynamically adjust control parameters in real-time based on system feedback, leading to improved performance, efficiency, and reliability. This paper provides a comprehensive review of AI-based adaptive control systems for power electronics, including machine learning algorithms, adaptation mechanisms, implementation considerations, applications, and future research directions. Through an in-depth analysis of existing literature and case studies, this paper highlights the advantages, challenges, and potential opportunities associated with AI-based adaptive control in power electronics. Moreover, it identifies emerging trends and areas for further investigation, paving the way for advancements in intelligent control solutions for future energy systems.