Abstract
A switched reluctance motor torque ripple reduction scheme using a B-spline neural network (BSNN) is presented. Closed-loop torque control can be implemented using an on-line torque estimator. Due to the local weight updating algorithm used for the BSNN, an appropriate phase current profile for torque ripple reduction can be obtained on-line in real time. It has good dynamic performance with respect to changes in torque demand. The scheme does not require high-bandwidth current controllers. Simulation and experimental results demonstrate the validity of the scheme. © 2006 IEEE.
| Original language | English |
|---|---|
| Pages (from-to) | 1445-1453 |
| Number of pages | 9 |
| Journal | IEEE Transactions on Industry Applications |
| Volume | 42 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - Nov 2006 |
Keywords
- Neural networks
- Reluctance motors
- Torque control
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