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

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Open Access

|Jun 2013

[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.
Open DOI Search in Google Scholar
[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.
Open DOI Search in Google Scholar
[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.
Search in Google Scholar
[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.
Open DOI Search in Google Scholar
[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.
Open DOI Search in Google Scholar
[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.
Open DOI Search in Google Scholar