Multi-step Model Predictive Current Control Of Permanent Magnet Synchronous Motor With Model Self-correction

The model predictive current control method has advantages of fast dynamic response and flexible and variable constraints,which have attracted wide attention of many scholars.The op-timal voltage vector selected by the model predictive current control method is optimal within a control period.This method does not take into account the influence of the future multiple con-trol periods on the system control peformance,which may result in poor steady-state perfor-mance of the system.In order to solve this problem,this paper takes a permanent magnet syn-chronous motor as the control object and studies a multi-step model predictive current control method,which considers the optimal information contained in the optimal voltage vector and other voltage vectors to ensure that the selected voltage vector is optimal within two control periods.The model predictive current control method relies on the predictive model.The accu-racy of the permanent magnet synchronous motor parameters directly affects the control per-formance of the system.In order to improve the parameter robustness of multi-step model pre-dictive current control method,a multi-step model predictive current control with model self-correction method is studied.The inductance observation algorithm is used to observe the stator inductance equivalent value and correct the prediction model.The voltage vector is selected by the multi-step model current control algorithm and acted on the inverter.In order to verify the feasibility and effectiveness of the multi-step model predictive cur-rent control with model self-correction method,this paper takes a permanent magnet synchron-ous motor as the control object.The proposed method is simulated in MATLAB simulation software and experimented two-level voltage inverter platform respectively.The simulation and experimental results show that compared with the model predictive current control method,the multi-step model predictive current control with model sel f-correction and the multi-step model predictive current control both reduce current ripple.Compared with the model predictive cur-rent control and the multi-step model predictive current control methods,the multi-step model predictive current control with model self-correction method reduces the sensitivity of the sys-tem to the stator inductance and improves the parameter robustness.In addition,the average switching frequency of the multi-step model predictive current control with model self-correction method is the same as the model predictive current control and multi-step model pre-dictive current control methods basically.