Title :
An interpretation of Preisach-Krasnoselskii hysteresis model with the use of artificial neural networks
Author_Institution :
Dept. of Math, Phys. & Comput. Sci., Ryerson Univ., Toronto, Ont., Canada
Abstract :
Summary form only given. This paper presents the application of artificial neural networks to implement an accurate magnetic hysteresis model based on the mathematical definition provided Preisach-Krasnoselskii (P-K) model. Accurate modeling of hysteresis is essential for both the design and the performance evaluation of electromagnetic devices. This paper shows that artificial neural networks (ANN) provide the natural setting whereby the P-K model can be successfully implemented.
Keywords :
magnetic hysteresis; neural nets; physics computing; Preisach-Krasnoselskii hysteresis model; artificial neural networks; electromagnetic devices; Artificial intelligence; Artificial neural networks; Computer networks; Context modeling; Lakes; Magnetic analysis; Magnetic hysteresis; Magnetization processes; Neural networks; Physics;
Conference_Titel :
Magnetics Conference, 2002. INTERMAG Europe 2002. Digest of Technical Papers. 2002 IEEE International
Conference_Location :
Amsterdam, The Netherlands
Print_ISBN :
0-7803-7365-0
DOI :
10.1109/INTMAG.2002.1001348