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Full and reduced order extended kalman filter for speed estimation in induction motor drives: a comparative study
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Orientador(es)
Resumo(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.
Descrição
Palavras-chave
Kalman filters Covariance matrices Induction motor drives Machine vector control Parameter estimation Reduced order systems Rotors Stators Torque Tuning
Contexto Educativo
Citação
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.
Editora
IEEE