Estimation error and high frequency ripple in the traditional sliding-mode observer control of a PMSM are problems for which this paper proposes a method of combining the extended Kalman filter with an improved sliding mode observer to replace the traditional one. First, the error between the estimated stator current and the actual value and the back-EMF are calculated according to the mathematical model of the sliding mode observer of PMSM. Then, the output variables are calculated according to the EKF state equation of the motor, which realizes on-line parameter adjustment and reduces parameter estimation errors, thereby improving steady-state and dynamic performance of the system. Finally, a simulation and hardware experimental platform are built to verify the proposed method. The results show that the optimized sliding mode observer control reduces the chattering of the system. System disturbance is reduced by 70% when the voltage parameters of the regulator are changed, and the method enables the PMSM to have better reliability and tracking performance. This work is supported by the National Natural Science Foundation of China (No. 61403068) and the Natural Science Foundation of Hebei Province (No. F2016501080).