Universal hysteresis identification using extended Preisach neural network
Hysteresis phenomena have been observed in different branches of physics and
engineering sciences. Therefore, several models have been proposed for hysteresis …
engineering sciences. Therefore, several models have been proposed for hysteresis …
Hysteresis identification using extended preisach neural network
Hysteresis phenomena have been observed in different branches of physics and
engineering sciences. Therefore several models have been proposed for hysteresis …
engineering sciences. Therefore several models have been proposed for hysteresis …
Diagonal recurrent neural network-based hysteresis modeling
G Chen, G Chen, Y Lou - IEEE Transactions on Neural …, 2021 - ieeexplore.ieee.org
The Preisach model and the neural networks are two of the most popular strategies to model
hysteresis. In this article, we first mathematically prove that the rate-independent Preisach …
hysteresis. In this article, we first mathematically prove that the rate-independent Preisach …
Hysteresis nonlinearity identification using new Preisach model‐based artificial neural network approach
Preisach model is a well‐known hysteresis identification method in which the hysteresis is
modeled by linear combination of hysteresis operators. Although Preisach model describes …
modeled by linear combination of hysteresis operators. Although Preisach model describes …
Hysteresis simulation using least-squares support vector machine
M Farrokh - Journal of Engineering Mechanics, 2018 - ascelibrary.org
Hysteresis is a highly nonlinear phenomenon, which is observed in different branches of
sciences. The behavior of the hysteretic systems is usually controlled by some …
sciences. The behavior of the hysteretic systems is usually controlled by some …
Adaptive simulation of hysteresis using neuro-Madelung model
Hysteretic phenomena have been observed in different branches of engineering sciences.
Although each of them has its own characteristics, Madelung's rules are common among …
Although each of them has its own characteristics, Madelung's rules are common among …
An explainable neural network integrating Jiles-Atherton and nonlinear auto-regressive exogenous models for modeling universal hysteresis
L Ni, J Chen, G Chen, D Zhao, G Wang… - … Applications of Artificial …, 2024 - Elsevier
The inherent nonlinear and memory-dependent input-output characteristics of piezoelectric
actuators pose challenges to the precision of piezoelectric positioning systems. In order to …
actuators pose challenges to the precision of piezoelectric positioning systems. In order to …
Development of a novel diagonal-weighted Preisach model for rate-independent hysteresis
This article develops an alternative approach in modeling a hysteresis using Preisach
model. A Preisach model is demonstrated geometrically by an inverted triangle, namely …
model. A Preisach model is demonstrated geometrically by an inverted triangle, namely …
[HTML][HTML] Deep neural networks for the efficient simulation of macro-scale hysteresis processes with generic excitation waveforms
S Quondam-Antonio, F Riganti-Fulginei… - … Applications of Artificial …, 2023 - Elsevier
An effective and performing hysteresis model, based on a deep neural network, with the
capability to reproduce the evolution of magnetization processes under arbitrary waveforms …
capability to reproduce the evolution of magnetization processes under arbitrary waveforms …
Hysteresis nonlinearity identification by using RBF neural network approach
M Firouzi, SB Shouraki… - 2010 18th Iranian …, 2010 - ieeexplore.ieee.org
In systems with hysteresis behavior like magnetic cores, Piezo actuators, Shape Memory
Alloy (SMA), we essentially need an accurate modeling of hysteresis either for design or …
Alloy (SMA), we essentially need an accurate modeling of hysteresis either for design or …