A Novel Current Predictive Control Based on Fuzzy Algorithm for PMSM

The fast and stable current inner loop in the permanent-magnet synchronous motor (PMSM) control system is the key factor that ensures the torque control performance of the motor. The deadbeat model predictive control strategy can achieve fast dynamic response, but it depended on the accurate mathematical model of the motor. When the model parameter in the predictive controller has mismatched with real system, the static error or oscillations will occur in the steady state. Therefore, a novel current predictive control based on the fuzzy algorithm is proposed in this paper. The novel control strategy contained a predictive controller, a proportional-integral (PI) compensation link, a magnetic flux observer, and a fuzzy controller. According to the operation state of the motor and the model parameter mismatch of the controller, the fuzzy algorithm can adjust the effect of compensation link by weight coefficient in real time. The dynamic performance of the proposed method is guaranteed compared with the traditional deadbeat predictive current control based on the space vector pulsewidth modulation (SVPWM). When the model parameter mismatch of controller is occurred, the weight of the PI compensation link is enhanced, and the static error or oscillation of the motor system can be eliminated.