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PARAMETER IDENTIFICATION TECHNIQUES FOR INDUCTION MOTOR DRIVES
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| Author(s) |
D. J. Atkinson; P. P. Acarnley; J. W. Finch |
| Abstract |
The Kalman Filter (KF) in its basic form is a state estimator and can be applied to the direct field orientation problem. The paper shows how this filter combines information from the plant model with output measurements to produce an optimal estimate of the unmeasured states. Simulation results for the KF used as a rotor current state estimator are presented and indicate how the filter could be used in a direct vector control system. As the KF can deal with a time varying linear plant model, then the rotor current can be estimated while the rotor speed is varying. lt is shown that the extended Kalman filter (EKF) overcomes the unmeasureable rotor state problem by providing simultaneous state and parameter estimates, using linearisation about the most recent estimate. Simulation results for rotor current / rotor resistance estimation are presented. The extended Kalman filter should always be used with caution as divergence may occur if the assumptions required for the linearisation process are not upheld in the application. |
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| Filename: | Unnamed file |
| Filesize: | 3.438 MB |
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| Type |
Members Only |
| Date |
Last modified 2021-02-12 by System |
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