Speed Estimation by EKF with Parameter Adaption

In the Permanent Magnet Synchronous Motor(PMSM) sensorless control system based on Extended Kalman Filter(EKF) algorithm, a set of fixed parameter of EKF algorithm is difficult to balance the dynamic and steady state performance of the system. Based on the analysis of the influence of EKF parameters Q
₃
, R
₁
and R
₂
on the system performance, a parameter adaptive law is proposed by a hyperbolic tangent function for EKF algorithm to estimate the PMSM speed. The hyperbolic tangent function is a relationship function between the parameter and speed error. Then these three parameters can be adaptively adjusted to regulate the system speed response. The simulation results show that compared with the traditional EKF algorithm, this method can effectively reduce the steady state chattering and increase the speed response of the system.