Speed Control of Permanent Magnet Synchronous Machines: ANFIS Design and Performance Evaluation

Abstract

Permanent Magnet Synchronous Machines (PMSMs) are widely used in automation and robotics applications due to their high efficiency, low maintenance requirements, and favorable size-to-weight ratio compared to other motors. In many industrial applications, conventional microcontrollers like PID controllers are commonly employed, but their performance often suffers from variations in dynamic systems. To address these challenges, an intelligent controller based on artificial neural networks with fuzzy inference system (ANFIS) was developed for speed control of PMSMs. The performance of this smart controller was validated by comparing it with other control methods such as PID and fuzzy controllers. The results presented in this paper demonstrate the capability of the proposed intelligent controller to effectively regulate PMSM operation in applications where simplicity, reliability, and stability are crucial.