Long-Prediction-Horizon FCS-MPC of Six-Phase PMSM Motor Based on Merge Sorting Sphere Decoding

The control performance of model predictive control based motor drives can be enhanced as the prediction horizon increases, but at the expense of large computational burden. To solve this problem, this paper proposes a sphere decoding algorithm (SDA) based on merge sorting for the MPC-controlled six-phase PMSM drive. First, the form of the current predictive control optimization problem is reconstructed. Then, instead of depth-first strategy in conventional SDA, the search strategy of the search tree is changed to breadth-first. Meanwhile, the merge sorting algorithm is proposed in the horizontal comparison, which significantly simplifies the search process. In this way, the problem of heavy computational burden of MPC is solved. Meanwhile, the control performance is enhanced through long prediction horizon MPC. The experimental results verify the excellent performance of the proposed method.