A new approach for speed estimation in induction motor drives based on a reduced-order extended Kalman filter

Leite, Vicente; Araújo, Rui Esteves; Freitas, Diamantino Silva

http://hdl.handle.net/10198/2213

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Authors

Leite, Vicente

Araújo, Rui Esteves

Freitas, Diamantino Silva

Abstract(s)

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.

Keywords

Kalman filters Covariance matrices Induction motor drives Machine control Nonlinear filters Nonlinear filters Nonlinear filters Robust control Rotors

URI

http://hdl.handle.net/10198/2213

Citation

Leite, V.; Araújo, R.; Freitas, D. (2004). A new approach for speed estimation in induction motor drives based on a reduced-order extended Kalman filter. In IEEE International Symposium on Industrial Electronics. Ajaccio, Córcega.