๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Using neural networks in the identification of Preisach-type hysteresis models

โœ Scribed by Adly, A.A.; Abd-El-Hafiz, S.K.

Book ID
114549349
Publisher
IEEE
Year
1998
Tongue
English
Weight
138 KB
Volume
34
Category
Article
ISSN
0018-9464

No coin nor oath required. For personal study only.

๐Ÿ“œ SIMILAR VOLUMES

Hysteresis identification of polymethyla
Hysteresis identification of polymethylaniline-based ER fluid using Preisach model
โœ Y.M Han; S.C Lim; H.G Lee; S.B Choi; H.J Choi ๐Ÿ“‚ Article ๐Ÿ“… 2003 ๐Ÿ› Elsevier Science โš– 533 KB

This paper presents the identification of field-dependent hysteresis in an electrorheological (ER) fluid using the Preisach model. As a first step, polymethylaniline (PMA) particles are prepared and mixed with silicone oil to make an ER fluid. A Couette type electroviscometer is then employed to obt

Implementation of magnetostriction Preis
Implementation of magnetostriction Preisach-type models using orthogonally coupled hysteresis operators
โœ A.A. Adly; S.K. Abd-El-Hafiz ๐Ÿ“‚ Article ๐Ÿ“… 2008 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 246 KB

Magnetic materials exhibiting gigantic magnetostriction are currently being used in various actuator devices and vibration damping applications. Recently, a new family of efficient Preisach-type vector hysteresis models having coupled elementary operators has been introduced. The purpose of this pap