Strong parameters robustness model predictive current control method

Model predictive control is a kind of control method based on parameter model. However, in the actual system, the parameters of the motor may deviate from the parameters in the model due to the influence of various objective factors, leading to deterioration of the control performance. In this paper, a strong parameters robustness model predictive current control (MPCC) method for permanent-magnet synchronous motor (PMSM) is proposed. This method can observe the disturbance caused by parameter errors. The observed disturbance is substituted into the system model to improve the control performance. Simulation results show the proposed method can effectively eliminate the influence of the parameter disturbances on the control performance and decrease the parameter sensitivity of model predictive current control.