Full and reduced order extended kalman filter for speed estimation in induction motor drives: a comparative study

Leite, V.; Araújo, Rui Esteves; Freitas, Diamantino Silva

http://hdl.handle.net/10198/2212

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Authors

Leite, V.

Araújo, Rui Esteves

Freitas, Diamantino Silva

Abstract(s)

This paper presents a comparative study between a new approach for robust speed estimation in induction motor sensorless control, using a reduced order Extended Kalman Filter (EKF), and the one performed by the full order EKF. The new EKF algorithm uses a reduced order state-space model that is discretized in a particular and innovative way. In this case only the rotor flux components are estimated, besides the rotor speed, while the full order EKF also estimates stator current components. This new approach strongly reduces the execution time and simplifies the tuning of covariance matrices. The performance of speed estimation using both EKF techniques is compared with respect to computation effort, tuning of the algorithms, speed range including low speeds, load torque conditions and robustness relatively to motor parameter sensitivity.

Keywords

Kalman filters Covariance matrices Induction motor drives Machine vector control Parameter estimation Reduced order systems Rotors Stators Torque Tuning

URI

http://hdl.handle.net/10198/2212

Citation

Leite, V.; Araújo, R.; Freitas, D. (2004). Full and reduced order extended kalman filter for speed estimation in induction motor drives: a comparative study. In 35th IEEE Power Electronics Specialists Conference. Aachen, Germany. p.2293-2299.