Disturbance Pre-Estimation Based Receding Horizon Predictive Control for PMSM Drives

In this article, a disturbance pre-estimation based receding horizon prediction control (DPE-RHPC) method is proposed to address the limitations of traditional methods in terms of poor system dynamic performance and robustness caused by dynamic disturbances. The DPE-RHPC introduces a generalized receding horizon estimator (GRHE) to estimate the lumped disturbances and high-order derivatives in the velocity and current loops, thereby constructing a disturbance dynamic sequence that can predict the future behavior of disturbances. Combined with the multi-step predictive control method, it provides additional disturbance dynamic information for long horizon optimization problems without increasing computational burden. By utilizing the disturbance dynamic information and combining it with receding horizon optimization of predictive control, the prediction model is updated to improve prediction accuracy and demonstrate better control performance. The effectiveness of the proposed method is verified through simulation and experimental results.