Sensorless Control of Permanent Magnet Synchronous Motor Based on Fuzzy Super-Twisting Algorithm Sliding Mode Observer

To mitigate the chattering issue in sensorless control of permanent magnet synchronous motor (PMSM) caused by traditional sliding mode observer (SMO), this paper proposes a novel approach integrating the super-twisting algorithm with fuzzy control. The high-frequency chattering in SMO induces motor speed fluctuations, compromising system stability. To mitigate this, the super-twisting algorithm is employed to construct a super-twisting sliding mode observer (STASMO), where a saturation function sat(x) replaces the conventional switching function sgn(x), further minimizing chattering. Moreover, a Phase-Locked Loop (PLL) is integrated to enhance rotor angle tracking, thereby improving speed and position estimation accuracy. Furthermore, fuzzy logic theory is applied to dynamically adjust the gain using a fuzzy algorithm, enhancing system robustness. Simulation results show that, compared to traditional SMO and STASMO, the proposed FSTASMO achieves superior chattering suppression, higher estimation accuracy, and enhanced system stability.