Three-vector Based Low-complexity Model Predic-Tive Current Control With Reduced Steady-state Current Error For Permanent Magnet Synchronous Motor

Permanent magnet synchronous motor(PMSM)is widely used in the fields of aerospace and industrial manufacturing,due to its high power density,low loss and large torque inertia ratio.The model predictive current control has the advantages of fast dynamic response,easy implementation and no weight factor,so it is employed on PMSM.The three-vector based model predictive current control is an improved strategy of model predictive current control.The three-vector based model predictive current control strategy needs to optimize six combina-tions voltage vector in each sampling period to find the optimal voltage vector combinations.This process leads to large computation.At the same time,the three-vector based model predic-tive current control strategy is one model based control strategy.Therefore,there is steady-state current error under motor parameter mismatch.In order to solve the problems of large computa-tion and steady-state current error under motor parameter mismatch of three-vector based model predictive current control,a three-vector based low-complexity model predictive current control with reduced steady-state current error strategy for the permanent magnet synchronous motor drive system is studied in this paper.Firstly,the optimization process of optimal voltage vector combination is simplified to reduce the calculation amount of the three-vector based model pre-diction current control.The Luenberger observer is also introduced to observe the disturbance caused by motor parameter mismatch and unmodeled dynamics.The estimated lump disturb-ance is considered as compensation to the model to reduce steady-state current error caused by the motor parameter mismatch.In this paper,the simulation model of three-vector based low-complexity model predictive current control with reduced steady-state current error strategy is established by using MATLAB simulation software,and the simulation research is carried out.At the same time,the experimental research is carried out on two-level inverter-driven permanent magnet synchro-nous motor system.The simulation and experimental results show that,compared with the three-vector based model predictive current control strategy,the three-vector based low-complexity model predictive current control strategy can lower the computational burden.Compared with three-vector based low-complexity model predictive current control strategy,the three-vector based low-complexity model predictive current control with reduced steady-state current error strategy can reduce the steady-state current error caused by the motor param-eter mismatch,thus lower the dependence on the motor parameters.