基于模型预测控制的永磁同步电机参数辨识

为了达到永磁同步电机系统的动态响应快、稳态误差小、控制精度高的要求，采用模型预测控制设计转速控制器和电流控制器分别代替传统矢量控制系统的转速PI控制器和电流PI控制器，又因预测控制器较依赖于电机模型参数，易在电机运行过程产生参数失配现象，提出模型参考自适应方法对基于模型预测控制的永磁同步电机进行在线多参数辨识，以保证电机控制系统的性能要求，为了解决多参数辨识存在的欠秩问题，采用模型参考自适应分步辨识策略，以准确辨识电机模型参数，并在MATLAB/Simulink上仿真验证了所描述方法的有效性和可行性。

Parameter identification of PMSM based on model predictive control model

In order to achieve the requirements of fast dynamic response, small steady-state error, and high control accuracy of the permanent magnet synchronous motor system, the model predictive controller is used to replace the speed PI controller and current PI controller of the traditional vector control system. Depending on the parameters of the motor model , it is easy to cause parameter mismatch in the motor running process, which affects the control performance of the entire system. A model reference adaptive method is proposed to perform online step-by-step parameter identification of permanent magnet synchronous motors based on model predictive control to ensure motor control The performance requirements of the system , the simulation on MATLAB/Simulink verify the effectiveness and feasibility of the described method.