Robust Amplitude Control Set Model Predictive Control With Low-Cost Error for SPMSM Based on Nonlinear Extended State Observer

The finite control set model predictive current control involves addressing challenges related to greater cost function values and inaccurate current prediction models, which can adversely impact the steady-state performance in permanent magnet synchronous motor (PMSM). A robust amplitude control set model predictive current control method (RACSMPCC) is proposed in this study, aiming to enhance prediction accuracy and control precision. This method introduces a rotation coordinate system amplitude control set to reduce the cost function value and improve current control precision. Then, a nonlinear extended state observer (NESO) is employed to observe and compensate for comprehensive disturbances in the current prediction equation, thereby improving the accuracy of the current prediction. Simultaneously, a parameter configuration method in the complex frequency domain is proposed for NESO, and its influence on the disturbance rejection performance of the system is analyzed. Hardware experiments on a PMSM are conducted to validate the effectiveness of RACSMPCC in reducing cost function and improving current control accuracy.