Abstract
The application of neural techniques to the problem of torque ripple minimization in a switched reluctance motor (SRM) is presented. More conventional techniques for torque linearization 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 4 kW 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.
| Original language | English |
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| Title of host publication | Drives II |
| Pages | 1-6 |
| Number of pages | 6 |
| Volume | 6 |
| Edition | 377 |
| Publication status | Published - 1993 |
| Event | Proceedings of the 5th European Conference on Power Electronics and Applications - Brighton, Engl Duration: 13 Sept 1993 → 16 Sept 1993 |
Conference
| Conference | Proceedings of the 5th European Conference on Power Electronics and Applications |
|---|---|
| City | Brighton, Engl |
| Period | 13/09/93 → 16/09/93 |