This paper studies problems in traditional sliding mode observers (SMO) for permanent magnet synchronous motor (PMSM) sensorless control. These problems include large system chattering and weak anti-interference ability. A new sliding mode observer design method is proposed. This method combines fuzzy control and super-twisting theory. For the system oscillation phenomenon caused by the real-time adjustment of the approach rate in sliding mode control, the fuzzy control method is adopted to achieve the intelligent adjustment of state variables. Based on the distance between the system state quantity and the switching surface and its motion trend as the dual decision parameters of the fuzzy rule, by constructing an adaptive rate adjustment mechanism, the approaching process has dynamic response characteristics. The observation accuracy optimization and anti-interference performance improvement of the permanent magnet synchronous motor control system have been achieved. To verify the effectiveness of the designed algorithm, simulation experiments were constructed based on the MATLAB/Simulink platform for algorithm verification and analysis. The experiments tested the algorithms effectiveness. Results showed reduced system chattering. The observation systems stability and precision were enhanced.