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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Keerthipala, W.W.L. Duggal, B.R. Chun, M.H. |
| Copyright Year | 1998 |
| Description | Author affiliation: Sch. of Electr. & Comput. Eng., Curtin Univ. of Technol., Bentley, WA, Australia (Keerthipala, W.W.L.) |
| Abstract | Two types of observers (based on the linear and nonlinear model of the machine) have been used in torque and speed control of induction motor control schemes [K. B. Nordin et al. (1985), A. Bellini et al. (1985), D. S. Wijesundera et al. (1992)]. The reduced-order linear model of observer [D. S. Wijesundera et al. (1992)] is easy to implement in real time, but it does not give an accurate estimation of the rotor m.m.f. vector angle, /spl beta/, since the induction motor normally operates in the region of saturation. The nonlinear observer model which incorporates this effect of magnetic saturation of the induction motor cannot be practically implemented by using normal methods as it takes too long a time to estimate the angle /spl beta/. The implementation of the real-time torque/speed controller discussed in this paper is based on artificial neural networks (ANN) which take into account the effect of saturation and estimate the angle /spl beta/ in a few microseconds which is well within the real time deadline. |
| Starting Page | 282 |
| Ending Page | 288 |
| File Size | 341790 |
| Page Count | 7 |
| File Format | |
| ISBN | 0780348796 |
| DOI | 10.1109/PEDES.1998.1330029 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 1998-12-01 |
| Publisher Place | Australia |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Velocity control Induction motors Artificial neural networks Rotors Saturation magnetization Stators Torque control Vectors Magnetic circuits Equations |
| Content Type | Text |
| Resource Type | Article |
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