(untitled) (Conferencea, 2024)
Electric drive control systems are pivotal in modern engineering, with applications spanning automotive, industrial, and energy sectors. This article explores the evolving technologies in electric drive control systems, highlighting the significant advancements that have reshaped their design and functionality. We review the progression from traditional control methods, such as proportional-integral-derivative (PID) and vector control, to the integration of advanced artificial intelligence (AI) techniques. We discuss the impact of deep learning and reinforcement learning on real-time control and predictive maintenance, emphasizing their roles in optimizing energy use and improving fault detection. By synthesizing recent advancements and current research, this article offers a comprehensive overview of the state-of-the-art in electric drive control and its implications for future developments.