Simulation of Brushless DC Motor Control Based on an Improved Generalized Predictive Control Algorithm

The brushless DC motor (BLDCM) has a large speed tracking error during the load operation process, and the motor's performance is affected by load uncertainty. To solve these problems, we propose an improved generalized predictive control (GPC) algorithm for BLDCM control. We design a BLDCM control system and simulate the system based on the BLDCM model from the dSPACE ASM software. Simulation results show that the steady-state accuracy is 0.5 r/min when the motor reaches the steady state of 200 r/min from stillness, and the greatest speed fluctuation is 1.5 r/min when motor is disturbed by a sinusoidal load with 1 Nm amplitude. Compared with the conventional proportion-integral-derivative (PID) control and sliding mode control, the designed controller decreases the speed fluctuation to lower than 3.3%. Thus, the improved GPC algorithm controller can restrain the load disturbance effectively and improve the system speed tracking precision.