Parameter-Free Model Predictive Current Control for PMSM Based on Current Variation Estimation without Position Sensor

To remove parameter dependence in existing sensorless control strategies, a parameter-free model predictive current is proposed for permanent magnet synchronous motor without any position sensor. First, the variation during one sampling period analyzed and divided into two elements: natural attenuation forced response. Second, recursive least squares algorithm utilized to estimate future so that can be successfully executed paying no attention parameters. Meanwhile, information obtained by arc tangent function according estimated response of variation. At last, experimental results verify estimation errors rotor are reduced around 0.1 rad with smaller prediction error even at low speed where parameters required.