A review of nonlinear Kalman filter appling to sensorless control for AC motor drives

Sensorless control of AC motor drives, which takes the advantages of cost saving, higher reliability, and less hardware, has been developed for several decades. Among the existing speed sensorless control methods, nonlinear Kalman filter-based one has attached widespread attention due to its superb estimation accuracy and inherent resistibility to noise. However, the determination of noise covariance matrix and robustness of model uncertainties are still open issues in practice. A great number of studies try to solve these problems in resent years. This paper reviews the application of extended Kalman filter (EKF), unscented Kalman filter (UKF), and cubature Kalman filter (CKF) in speed sensorless control for AC motor drives. As an iterative algorithm, EKF has advantages in processor implementation. However, EKF suffers from the linearization error and model uncertainties when applying to sensorless control system. This paper presents the predominant improvements of EKF which is also applicative in UKF and CKF mostly.