Reinforcement Learning for Intelligent Control of AC Machine Drives: A Review
Nabil Farah,Gang Lei,Jianguo Zhu,Youguang Guo
TLDR
RL-based control of PMSM drives is reviewed, delving into fundamental concepts, machine learning types, and RL frameworks and challenges, drawbacks, and future directions for enhancing RL-based control methods are discussed.
摘要
Permanent magnet synchronous motors (PMSMs) are widely used in various industrial applications due to their high efficiency, compact size, and precise control capabilities. However, traditional control techniques often struggle to handle the nonlinearities and uncertainties associated with PMSM drives. Reinforcement learning (RL) based control approaches have offered a promising solution to address these challenges. This article reviews RL-based control of PMSM drives, delving into fundamental concepts, machine learning types, and RL frameworks. Challenges, drawbacks, and future directions for enhancing RL-based control methods are also discussed.