Abstract: Aiming at the problem that the traditional super-twisting algorithm based sliding-mode observer(STA-SMO) of permanent magnet synchronous motor uses fixed sliding mode parameters, which leads to large chattering and poor disturbance rejection ability, a sensorless control method of permanent magnet synchronous motor adaptive super-helical sliding mode observer is proposed. The sliding mode parameters can be updated in real time with the change of system speed. The stability of the proposed method is proved, and the higher estimation accuracy can be obtained by adjusting the sliding mode coefficient online. Aiming at the problem that the traditional vector control speed loop of permanent magnet synchronous motor adopts fixed parameter PI controller, which cannot meet the rapid response and parameter disturbance suppression ability of the system, the fuzzy PI controller is used in the speed outer loop, and the parameters of the PI controller are updated by the output of the fuzzy controller to enhance the robustness of the system. Finally, through simulation and experiment, it is verified that the fuzzy control based adaptive super-twisting algorithm sliding-mode observer for permanent magnet synchronous motor can effectively suppress system chattering, with high estimation accuracy and strong robustness.