Long-Prediction-Horizon FCS-MPC of Six-Phase Permanent Magnet Synchronous Motor Based on K-Best Sphere Decoding

Extending the prediction horizon can improve the control performance of the finite control set model predictive control (FCS-MPC) for motor drives. Nevertheless, the computational burden is inevitably increased. Meanwhile, the number of the prediction vectors for the six-phase motor is increased exponentially. To overcome this problem, this paper presents a K-best sphere decoding algorithm. The key is that the priority of the search strategy in the conventional sphere decoding is modified as breadth first. Simulation results are provided to prove the feasibility of the proposed method.