| |
NEURAL NETWORKS USED FOR TORQUE RIPPLE MINIMISATION FROM A SWITCHED RELUCTANCE MOTOR
| [View]
[Download]
|
| Author(s) |
D.S. Reay; T.C. Green; B.W. Williams |
| Abstract |
The application of neural techniques to the problem of torque ripple minimisation in a switched reluctance motor (SRM) is presented. More conventional techniques for torque linearisation and decoupling are reviewed, after which the application of a neural network to the problem is described. Results obtained experimentally and by simulation of a 4kW IGBT converter and 4-phase SRM are used to illustrate the approach. The networks used have been implemented using both digital signal processor (DSP) and field programmable gate array (FPGA) technologies. |
| Download |
| Filename: | Unnamed file |
| Filesize: | 3.299 MB |
|
| Type |
Members Only |
| Date |
Last modified 2019-05-09 by System |
| |
 |