Indirect Model Predictive Control of Matrix Converter Based on EKF Parameter Identification
In order to alleviate the intensive computational burden in the model predictive control(MPC)of the matrix converter,the MPC of the matrix converter was divided into the predictive control of the virtual rectifier and virtual inverter based on the equivalent indirect modulation of the matrix converter.Compared with the traditional direct MPC,the computational burden and execution time of the proposed strategy were reduced.Considering the issue of the high dependence of MPC on model parameters,the extended Kalman filter(EKF)was used to identify system model parameters online,thereby improving the robustness and anti-interference ability of MPC.The experimental results show that the proposed indirect MPC based on the extended Kalman filter parameter identification algorithm offers a good control performance on the load current and the grid side power factor control,and the dependence on the model parameters is reduced.
万方数据
维普
