Fuzzy Multi-vector Model Predictive Control of Permanent Magnet Synchronous Motor

Aiming at the jitter problem of using an optimal voltage vector in traditional model predictive control, a multi-vector finite control set model predictive control(MV-FCS-MPC) scheme based on fuzzy logic is proposed. Based on discrete space vector modulation, the proposed method synthesizes and selects the switching sequence of each sampling period by using the actual voltage vector and the new virtual voltage vector of the converter to improve the steady-state performance. Considering the large amount of computation of traditional model predictive control, a method of obtaining reference voltage vector directly from reference current based on deadbeat function is proposed, which reduces the amount of calculation of the proposed method. In view of the fact that the traditional PI control cannot adapt to the influence of external disturbance and parameter change on the system, the fuzzy logic controller is used to control the speed of the rotor in the outer loop speed, which improves the dynamic response of the speed and avoids the difficulty of setting the PI controller. Through simulation and experiment, and compared with the traditional FCS-MPC method, it shows that the proposed method has good dynamic and static performance and strong robustness.