Hysteresis modeling with adaptive neuro-fuzzy inference system

Ferroelectrics

Volumn 372, Issue 1 PART 2, 2008, Pages 54-65

  Mordjaoui, M ^a   Chabane, M ^b   Boudjema, B ^a   Daira, R ^a  

^a UNIVERSITY OF SKIKDA   (Algeria)

^b UNIVERSITY OF BATNA   (Algeria)

Author keywords

ANFIS modeling technique; Ferromagnetic core; Jiles Atherton model; Magnetic hysteresis

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; ANFIS MODEL; ELECTRICAL CIRCUIT; FERROMAGNETIC CORES; HYSTERESIS CURVE; HYSTERESIS MODELING; JILES ATHERTON MODEL; MAGNETIC COMPONENTS; MEASUREMENT DATA; MODEL ACCURACY; MODELING TECHNIQUE; NETWORK TRAINING; NEW APPROACHES; PERFORMANCE ANALYSIS; QUALITATIVE APPROACH; RMS ERRORS;

ELECTRIC NETWORK ANALYSIS; FERROMAGNETIC MATERIALS; FERROMAGNETISM; FUZZY INFERENCE; MAGNETIC DEVICES; MAGNETIC HYSTERESIS; MATERIALS; NEURAL NETWORKS;

FUZZY SYSTEMS;

EID: 75949123905     PISSN: 00150193     EISSN: 15635112     Source Type: Journal    
DOI: 10.1080/00150190802381761     Document Type: Conference Paper

References (12)

1. F. Preisach, "Über die magnetische nachwirkung" (in German). Zeitschrift für physik 94(5-6), 277 (1935).
2. D. C. Jiles and D. L. Atherton, "Theory of ferromagnetic hysteresis." J. Magn. Magn. Mater. 61, 48-60 (1986).
3. A. Salvini and F. Riganti Fulginei, "Genetic algorithms and neural networks loops." IEEE Trans. Magn. 38, 873-876 (2002).
4. Makaveev Dimitre, Luc Dupré, Wulf Marc De, and Melkebeek Jan, Combined Preisach-Mayergoyz-neural-network vector hysteresis model for electrical steel sheets. Journal of Applied Physics 93(10), 6638-6640 (2003).
5. M. Kuczmann and A. Iványi, "Neural Network Model of Magnetic Hysteresis" Compel, 21(3), 364-376 (2002).
6. J. J. Buckley and Y. Hayashi, Hybrid fuzzy neural nets are universal approximators. Proc IEEE Int Conf on Fuzzy Systems Orlando, FL, 238-243, (1994).
7. B. Kosko, "Fuzzy systems as universal approximators." Proc IEEE Int Conf on Fuzzy Systems, San Diego, CA, 1153-1162, (1992).
8. J. S. Jang, C.-T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing. Prentice Hall, (1997).
9. A. Abraham. "Neuro-Fuzzy Systems: State-of-the-art Modeling Techniques". In J. Mira and A. Prieto (Eds), Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence, Springer-Verlag, pp. 269-276, (2001).
10. The MathWorks, Inc, Fuzzy Logic Toolbox. The MathWorks, Inc., 1998.
11. J. S. Roger Jang and C. T. Sun, Neuro-Fuzzy Modeling And Control. Proceeding of the IEEE, 83(3) (1995).
12. Emilio Del Moral Hernandez, Carlos S. Muranaka, and José R. Cardoso, Identification of the Jiles-Atherton model parameters using random and deterministic searches. Physica B 275, 212-215 (2000).