| As an efficient and energy-saving motor,permanent magnet synchronous motor(PMSM)has the characteristics of small size,high power density,high power factor,high torque-current ratio,and is broadly applied in social production and life.The model predictive control method not only has the advantages of fast dynamic response and multiple application scenarios,but also can optimize multiple control objectives through strong constraint processing capability.Thus,the model predictive control method has become a hot spot in the control technology of PMSM.However,due to the need to establish predictive models,the model predictive control is highly dependent on parameters.So,obtaining real-time and accurate motor parameters is crucial for improving the control effectiveness of model predictive control.This paper studies model predictive control method and parameter identification of PMSM,and proposes an improved adaptive predictive control method.The main research work is as follows.First of all,the model predictive control method is analyzed,and the model predictive current control of PMSM is mainly studied.The feedback correction link is designed to correct and compensate the prediction error.The difference between the actual motor current value at the current moment and the predicted current value calculated at the last moment is set as the prediction error at the current time.This prediction error is fed back to the original prediction model.The closed-loop predictive control is realized and verified by the mathematical and incremental model of PMSM.The simulation and experimental results prove the effectiveness and feasibility of the feedback correction link to improve the predictive control performance of the model.Then,the parameter mismatch of PMSM is analyzed.The stator resistance,inductance and permanent magnet flux linkage are introduced,and the parameter identification method applied to the mathematical model and incremental model of PMSM is designed.The recursive least square method with forgetting factor is applied to the identification of PMSM.Taking the mismatch of motor inductance parameters as an example,the simulation verifies that the parameter identification algorithm designed in this paper can effectively track the parameter changes,identify the real-time and accurate electrical parameters online,and obtain the online PMSM model based on the data.Finally,an adaptive predictive control method of PMSM is summarized.The real-time and accurate PMSM model is obtained online through the designed parameter identifier,and it is used as the predictive model of the model predictive controller.Using the adaptive predictive control method can accelerate the response speed of the motor speed and reduce the steady-state error of the motor current.The influence of parameter change on predictive control is reduced. |
