Author(s): Araújo, Rui Esteves ; Freitas, Diamantino Silva ; Leite, Vicente
Date: 2003
Persistent ID: http://hdl.handle.net/10198/2218
Origin: Biblioteca Digital da UPB
Subject(s): Kalman filters; Induction motors; Machine vector control; Magnetic flux; Magnetic flux; Matrix algebra; Rotors; State-space methods; Statistical analysis; Stators Magnetic flux
A new online identification methodology for estimation of the rotor flux components and the main electrical parameters of vector controlled induction motors is presented in this paper. The induction motor model is referred to the rotor reference frame for estimation of rotor flux and rotor parameters, and referred to the stator reference frame to estimate stator parameters. The stator parameters estimation is achieved by a prediction error method based on a model structure described by a linear regression that is independent of rotor speed and rotor parameters. The rotor flux components and rotor parameters are estimated by a reduced order extended Kalman filter, using a 4th-order state-space model structure where the state equation is described by matrices that are diagonal and independent of rotor speed as well as stator parameters. Both methods work in a boot-strap manner.
