This paper proposes a dual-vector model predictive torque control (MPTC) method for a permanent magnet synchronous motor (PMSM)-driven system with disturbance compensation and extended Kalman filter (EKF) to improve the anti-interference capability and torque control accuracy. First, an extended state observer (ESO) is used to estimate the total disturbance, and a speed controller based on state feedback and disturbance compensation is constructed to achieve high-precision speed tracking. Next, an EKF is designed to perform online identification of the stator resistance and inductance parameters, which improves the robustness to parameter variations. Finally, based on the predictive model with the updated parameters, a dual-vector MPTC method is developed to obtain the optimal voltage vector combination, ensuring precise torque control and robust stability. Simulation results demonstrate that the proposed method significantly improves both tracking and disturbance rejection performance in steady-state and transient aspects, as well as robustness.

permanent magnet synchronous motor, extended Kalman filter, extended state observer, dual-vector model predictive torque control