Have a personal or library account? Click to login
Offline and Online Modelling of Switched Reluctance Motor Based on RBF Neural Networks Cover

Offline and Online Modelling of Switched Reluctance Motor Based on RBF Neural Networks

By: Jun Cai and  Zhiquan Deng  
Open Access
|Jun 2013

References

  1. [1] CHEN, H. J.-JIANG, D. Q.-YANG, J.-SHI, L. X. : A New Analytical Model for Switched Reluctance Motors, IEEE Transactions on Magnetics 45 (2009), 3107-3113.10.1109/TMAG.2009.2015876
  2. [2] MAO, S. H.-DORRELL, D.-TSAI, M. C. : Fast Analytical Determination of Aligned and Unaligned Flux Linkage in Switched Reluctance Motors Based on a Magnetic Circuit Model, IEEE Transactions on Magnetics 45 (2009), 2935-2942.10.1109/TMAG.2009.2016087
  3. [3] LYONS, J. P.-MacMINN, S. R.-PRESTON, M. A. : Flux/ Current Methods for SRM Rotor Position Estimation, Conf. Rec. IEEE-IAS Annu. Meeting, 1991, pp. 482-487.
  4. [4] CHEOK, A.-ERTUGRUL, N. : High Robustness and Reliability of Fuzzy Logic Based Position Estimation for Sensorless Switched Reluctance Motor Drives, IEEE Transactions on Power Electronics 15 (2000), 319-334.10.1109/63.838105
  5. [5] MESE, E.-TORREY, D. A. : An Approach for Sensorless Position Estimation for Switched Reluctance Motors using Artificial Neural Networks, IEEE Transactions on Power Electronics 17 (2002), 66-75.10.1109/63.988671
  6. [6] LIN, Z.-REAY, D. S. : Online Modelling for Switched Reluctance Motors using B-Spline Neural Networks, IEEE Transaction Industrial Electronic 54 (2007), 3317-3322.10.1109/TIE.2007.904009
DOI: https://doi.org/10.2478/jee-2013-0027 | Journal eISSN: 1339-309X | Journal ISSN: 1335-3632
Language: English
Page range: 186 - 190
Published on: Jun 8, 2013
In partnership with: Paradigm Publishing Services
Publication frequency: 6 issues per year

© 2013 Jun Cai, Zhiquan Deng, published by Slovak University of Technology in Bratislava
This work is licensed under the Creative Commons License.