Finite Control Set Model Predictive Control Strategy For Permanent Magnet Synchronous Motor Based On Extended Kalman Filter

The finite control set model predictive control(FCS-MPC)of permanent magnet synchronous motor(PMSM)has the advantages of easy to deal with constrained optimization problems and good dynamic performance,but it still has some problems,such as strong parameter dependence,difficult to adjust the weighting factor,large amount of algorithm calculation and so on.Therefore,this thesis studies the above problems.Firstly,in order to solve the problem of parameter dependence in the finite control set model predictive current control(FCS-MPCC)of PMSM,this thesis introduces the incremental prediction model without flux linkage.There is no flux linkage parameter in the incremental prediction model,and the prediction error caused by resistance mismatch is very small,which can be ignored.On this basis,this thesis proposes an incremental model predictive current control strategy based on extended Kalman filter(EKF),ignores the influence of resistance,takes the q-axis incremental equation as the state equation,uses extended Kalman filter to identify the inductance online and update it in real time in the model,which improves the parameter robustness of the control strategy.Secondly,aiming at the problem that it is difficult to adjust the weighting factor in the traditional finite control set model predictive torque control(FCS-MPTC)of PMSM,the deadbeat control is used for the torque and stator flux amplitude to obtain the reference voltage vector,and the tracking of torque and stator flux amplitude is transformed into the tracking of reference voltage vector.This thesis proposes a method to quickly select the voltage vector.The zero vector region is established in the spatial voltage vector diagram.When the reference voltage vector is located in the zero vector region,the zero vector is selected as the optimal voltage vector.When the reference voltage vector is located outside the zero vector region,the sector is judged according to the position angle of the reference voltage vector,The non-zero vector in the sector is selected as the optimal voltage vector.At the same time,in order to reduce the parameter sensitivity of the control strategy,the extended Kalman filter algorithm is used to identify the resistance and inductance parameters online and feed them back to the model,so as to avoid the problem of poor control effect caused by parameter mismatch.Finally,simulation and experiment are carried out on the control system of PMSM with two-level inverter to verify the superiority of the proposed control strategy.