Abstract
A novel on-line instant torque estimation scheme for a switched reluctance motor (SRM) is presented. In the proposed method, an adaptive B-spline neural network is used to learn the non-linear flux-linkage and torque characteristics of a SRM. Due to the local nature of its generalisation properties, the training of the B-spline neural network is accomplished on-line and in real-time, and the system does not require a priori knowledge of the machine's electromagnetic characteristics. The potential of the method is demonstrated successfully in simulation and experimentally using a 300W 12/8 3-phase SRM.
Original language | English |
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Title of host publication | Proceedings of the 29th Annual Conference of the IEEE Industrial Electronics Society, 2003 |
Pages | 1033-1037 |
Number of pages | 5 |
Volume | 2 |
DOIs | |
Publication status | Published - 2003 |
Event | 29th Annual Conference of the IEEE Industrial Electronics Society - Roanoke, VA, United States Duration: 2 Nov 2003 → 6 Nov 2003 |
Conference
Conference | 29th Annual Conference of the IEEE Industrial Electronics Society |
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Country/Territory | United States |
City | Roanoke, VA |
Period | 2/11/03 → 6/11/03 |
Keywords
- Neural network
- Switched reluctance motors
- Torque estimation