| |
Neural Network Based Estimation of the Flux Space Vector Angle for an Indirect Field Oriented Control Independant form Rotor Resistance Variations
| [View]
[Download]
|
| Author(s) |
A. Cataliotti; V. Cecconi; M. Cirrincione; A. Flaccomio |
| Abstract |
The aim of the paper is to obtain an indirect field oriented control scheme independant from rotor resistance changes by means of an Artifial Neural-Network estimation of the rotor flux space vector angle. This estimation is based on two non-recursive supervised neural networks. The training phase has been carried out off-line using an informative enough training set. Drive system simulations have shown improved dynamical responses as a consequence of the robustness of such a neural estimation with regard to rotor resistance variations, resulting form the generalisation properties of supervised neural networks. |
| Download |
| Filename: | EPE1999 - PP00863 - Cataliotti.pdf |
| Filesize: | 225.8 KB |
|
| Type |
Members Only |
| Date |
Last modified 2004-04-08 by System |
| |
 |