Qualitative Ferromagnetic Hysteresis Modeling
作者： M. Mordjaoui , M. Chabane , B. Boudjema , R. Daira
DOI: 10.3844/JCSSP.2007.399.405
关键词:
摘要: In determining the electromagnetic properties of magnetic materials, hysteresis modeling is high importance. Many models are available to investigate those characteristics but they tend be complex and difficult implement. A new qualitative model for ferromagnetic core presented, based on function approximation capabilities adaptive neuro-fuzzy inference system (ANFIS). The proposed ANFIS combined neural network fuzzy logic approach can restored curve with a little RMS error. accuracy was good easily adapted requirements application by extending or reducing training set thus required amount measurement data.
thescipub.com参考文章(18)
J.-S.R. Jang, Self-learning fuzzy controllers based on temporal backpropagation IEEE Transactions on Neural Networks. ,vol. 3, pp. 714- 723 ,(1992) , 10.1109/72.159060
J.-S.R. Jang, Chuen-Tsai Sun, Neuro-fuzzy modeling and control Proceedings of the IEEE. ,vol. 83, pp. 378- 406 ,(1995) , 10.1109/5.364486
P.R. Wilson, J.N. Ross, A.D. Brown, Optimizing the Jiles-Atherton model of hysteresis by a genetic algorithm IEEE Transactions on Magnetics. ,vol. 37, pp. 989- 993 ,(2001) , 10.1109/20.917182
A. Salvini, F.R. Fulginei, Genetic algorithms and neural networks generalizing the Jiles-Atherton model of static hysteresis for dynamic loops IEEE Transactions on Magnetics. ,vol. 38, pp. 873- 876 ,(2002) , 10.1109/20.996225
M. Kuczmann, A. Ivanyi, A new neural-network-based scalar hysteresis model IEEE Transactions on Magnetics. ,vol. 38, pp. 857- 860 ,(2002) , 10.1109/20.996221
J.J. Buckley, U. Hayashi, Hybrid fuzzy neural nets are universal approximators world congress on computational intelligence. pp. 238- 243 ,(1994) , 10.1109/FUZZY.1994.343759
P. Del Vecchio, A. Salvini, Neural network and Fourier descriptor macromodeling dynamic hysteresis IEEE Transactions on Magnetics. ,vol. 36, pp. 1246- 1249 ,(2000) , 10.1109/20.877666
Lotfi A. Zadeh, Fuzzy sets Fuzzy sets, fuzzy logic, and fuzzy systems. pp. 394- ,(1996)
Jang J.S.R., ANFIS: ADAPTIVE-NETWORK-BASED FUZZY INFERENCE SYSTEMS IEEE TRANSACTIONS ON SYSTEMS, MAN AND CYBERNETICS. ,vol. 23, pp. 665- 685 ,(1993)
Mahmoud Saghafifar, Anjan Kundu, Andrew Nafalski, Dynamic magnetic hysteresis modelling using Elman recurrent neural network International Journal of Applied Electromagnetics and Mechanics. ,vol. 13, pp. 209- 214 ,(2002) , 10.3233/JAE-2002-323