Neural network model of magnetic hysteresis

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering

Volumn 21, Issue 3, 2002, Pages 364-376

  Kuczmann, Miklós ^a   Iványi, Amália ^a  

^a BUDAPEST UNIVERSITY OF TECHNOLOGY AND ECONOMICS   (Hungary)

Author keywords

Hysteresis; Magnetic forces; Neural networks

Indexed keywords

ALGORITHMS; APPROXIMATION THEORY; COMPUTER SIMULATION; KNOWLEDGE BASED SYSTEMS; MAGNETIC SUSCEPTIBILITY; MAGNETIZATION; NEURAL NETWORKS; PROBLEM SOLVING;

KNOWLEDGE-BASED ALGORITHMS;

MAGNETIC HYSTERESIS;

EID: 0036306367     PISSN: 03321649     EISSN: None     Source Type: Journal    
DOI: 10.1108/03321640210423289     Document Type: Article

References (17)

1. Adly, A.A. and Abd-El-Hafiz, S.K. (1998), “Using Neural Networks in the Identification of Preisach-Type Hysteresis Models”, IEEE Trans. on Magn., Vol. 34, pp. 629–35.
2. Adly, A.A., Abd-El-Hafiz, S.K. and Mayergoyz, I.D. (2000), “Identification of vector Preisach models from arbitrary measured data using neural networks”, Journal of Applied Physics, Vol. 87, pp. 6821–3.
3. Christodoulou, C. and Georgiopoulos, M. (2001), Applications of Neural Networks in Electromagnetics, Artech House, Norwood.
4. Füzi, J. (1997), “Parameter Identification in Preisach Model to Fit Major Loop Data”, in, Applied Electromagnetics and Computational Technology, in Series of Studies in Applied Electromagnetics and Mechanism, IOS Press, Vol. 11 pp. 77–82.
5. Füzi, J., Helerea, E. and Iványi, A. (1998), Experimental Construction of Preisach Models for Ferromagnetic Cores, PCIM/PQ, Nürnberg.
6. Ivanyi, A. (1997), Hysteresis Models in Electromagnetic Computation, Akadémia Kiadó, Budapest.
7. Kuczmann, M. and Iványi, A. (2000a), “A New Neural Network Model for Magnetic Hysteresis”, in, Proceedings of the 9th International IGTE Symposium on Numerical Field Calculation in Electrical Engineering and European TEAM Workshop, Graz, Austria pp. 369–74.
8. Kuczmann, M. and Iványi, A. (2000b), “Neural Network Simulation of Scalar Magnetic Hysteresis”, in, Proceedings of the 4th Japan-Central Europe Joint Workshop on Energy and Information in Non-Linear Systems, November 10–12, Brno, Czech Republic pp. 102–5.
9. Kuczmann, M. and Iványi, A. (2001a), “Neural Network Based Scalar Hysteresis Model”, in, Proceedings of the 10th International Symposium on Applied Electromagnetics and Mechanics, May 13–16, Tokyo, Japan pp. 493–4.
10. Kuczmann, M. and Iványi, A. (2001b), “Scalar Hysteresis Model Based on Neural Network”, in, IEEE International Workshop on Intelligent Signal Processing, May 24–25, Budapest, Hungary pp. 143–8.
11. Kuczmann, M. Iványi, A. (2001c), A New Neural Network Based Scalar Hysteresis Model, Record of the 13th Compumag Conference on the Computation of Electromagnetic Fields, Lyon-Evian, France, July 2–5, Vol.2/4, PC1-9, pp. 30–1.
12. Kuczmann, M. Iványi, A. Füzi, J. (2001d), Scalar and Vector Hysteresis Model with Neural Networks, Physica B (megjelenés alatt).
13. Kuczmann, M. and Iványi, A. (2001e), “Scalar Neural Network Hysteresis Model”, in, Proceedings of the XI. Internatonal Symposium on Theoretical Electrical Engineering, August 19–22 ISTET131, Linz Austria.
14. Mayergoyz, I.D. (1991), Mathematical Models of Hysteresis, Springer-Verlag, New York.
15. Serpico, C. and Visone, C. (1998), “Magnetic Hysteresis Modeling via Feed-Forward Neural Networks”, IEEE Trans. on Magn., Vol. 34, pp. 623–8.
16. V. Rao Vemuri (1992), Artificial Neural Networks, Concepts and Control Applications, IEEE Computer Soc. Pr., Los Alamos, California.
17. Visone, C., Serpico, C., Mayergoyz, I.D., Huang, M.W. and Adly, A.A. (1999), “Neural-Preisach-Type Models and Their Application to the Identification of Magnetic Hysteresis From Noisy Data”, Physica B Condensed Matter, Vol. 275, pp. 223–7.