In order to realize the speed sensorless control of the controllable excitation linear synchronous motor (CELSM) feed system of the CNC machine, it is necessary to accurately obtain the motor speed and magnetic pole position information. A method for estimating the speed and position of CELSM by using the armature winding voltage and current of the motor was proposed, namely the extended Kalman filtering algorithm based on HSymboleB@ (HEKF). The current iα,iβ, the speed v and the electrical angle θe of the mover in the αβ coordinate system were selected as the state variables to establish the state equation of the HEKF observer, and the state equation was discretized. Based on extended Kalman filtering, a filtering upper bound function was designed to limit and minimize the upper bound of the estimation error, which effectively improves the robustness of the observer to the noise. The simulation shows that the speed and position estimation of the HEKF algorithm is closer to the actual value than the EKF algorithm in the dynamic phase; when the speed is abrupt, the robustness of HEKF algorithm is more robust than the EKF algorithm