Abstract
Rotor position sensorless control of the permanent magnet synchronous motor (PMSM) typically requires knowledge of the PMSM structure and parameters, which in some situations are not readily available or may be difficult to obtain. Due to this limitation, an alternative approach to rotor position sensorless control of the PMSM using a diagonally recurrent neural network (DRNN) is considered. The DRNN is a dynamic mapping, requires fewer neurons, and converges quickly compared to feedforward and fully recurrent neural networks. Experimental results of the proposed neural observer to PMSM rotor estimation are presented.
| Original language | English (US) |
|---|---|
| Pages | 2441-2445 |
| Number of pages | 5 |
| State | Published - 2000 |
| Event | Proceedings of the 2000 Power Engineering Society Summer Meeting - Seattle, WA, United States Duration: Jul 16 2000 → Jul 20 2000 |
Other
| Other | Proceedings of the 2000 Power Engineering Society Summer Meeting |
|---|---|
| Country | United States |
| City | Seattle, WA |
| Period | 7/16/00 → 7/20/00 |
All Science Journal Classification (ASJC) codes
- Electrical and Electronic Engineering
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Batzel, T. D., & Lee, K. Y. (2000). A diagonally recurrent neural network approach to sensorless operation of the permanent magnet synchronous motor. 2441-2445. Paper presented at Proceedings of the 2000 Power Engineering Society Summer Meeting, Seattle, WA, United States.