An improved nonlinear model predictive direct speed control of permanent magnet synchronous motors

Field-oriented control (FOC) is one of the most effective techniques widely used in industry for speed control of permanent magnet synchronous motor. However, the main drawback of such linear controller with cascade structure is its limited bandwidth to avoid large overshoots and ringing. This problem significantly increases the switching frequency. To overcome this problem, this paper proposes a novel nonlinear model predictive control (NMPC) scheme for direct speed control of the permanent magnet synchronous motor to minimize the inverter switching frequency. The proposed NMPC suggests different sampling times in the prediction process to increase the prediction horizon. It also presents an incremental algorithm to reduce the computational time, rendering it suitable for real-time applications. The performance of the proposed NMPC method is compared with an optimum FOC scheme via simulations performed by MATLAB/Simulink software. The results show that the proposed method provides improved speed tracking performance as well as lower electromagnetic torque ripple. In addition, the inverter average switching frequency with the proposed control approach is almost 10 times lower than that with the FOC approach.