Author(s):
Leite, Vicente ; Araújo, Rui Esteves ; Freitas, Diamantino Silva
Date: 2004
Persistent ID: http://hdl.handle.net/10198/2213
Origin: Biblioteca Digital da UPB
Subject(s): Kalman filters; Covariance matrices; Induction motor drives; Machine control; Nonlinear filters; Nonlinear filters; Nonlinear filters; Robust control; Rotors
Description
This paper presents and proposes a new approach to achieve robust speed estimation in induction motor sensorless control. The estimation method is based on a reduced-order extended Kalman filter (EKF), instead of a full-order EKF. The EKF algorithm uses a reduced-order state-space model structure that is discretized in a particular and innovative way proposed in this paper. With this model structure, only the rotor flux components are estimated, besides the rotor speed itself. Important practical aspects and new improvements are introduced that enable us to reduce the execution time of the algorithm without difficulties related to the tuning of covariance matrices, since the number of elements to be adjusted is reduced.