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 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 …
Neural network based identification of Preisach-type hysteresis in piezoelectric actuator using hysteretic operator
X Zhao, Y Tan - Sensors and Actuators A: Physical, 2006 - Elsevier
A neural network based approach of identification for Preisach-type hysteresis is proposed.
In this method, a hysteretic operator is introduced to transform the multi-valued mapping of …
In this method, a hysteretic operator is introduced to transform the multi-valued mapping of …
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 …
Improved EHM-based NN hysteresis model
L Ma, Y Tan, Y Chu - Sensors and Actuators A: Physical, 2008 - Elsevier
An improved EHM-based hysteresis model is proposed in this paper. In this scheme, neural
networks are employed to implement the mapping between the input and output of …
networks are employed to implement the mapping between the input and output of …
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 …
A neural networks model for hysteresis nonlinearity
L Chuntao, T Yonghong - Sensors and Actuators A: Physical, 2004 - Elsevier
This paper presents a new approach for modeling hysteresis nonlinearity in piezo-actuators.
Under a mild assumption, a mapping, which can be approximated by multi-layer neural …
Under a mild assumption, a mapping, which can be approximated by multi-layer neural …
Adaptive modeling of highly nonlinear hysteresis using preisach neural networks
M Farrokh, A Joghataie - Journal of Engineering Mechanics, 2014 - ascelibrary.org
In this paper, a new type of multilayer feedforward neural network has been proposed based
on inspiration from the Preisach model, which has been called the Preisach neural network …
on inspiration from the Preisach model, which has been called the Preisach neural network …
Modeling hysteresis and its inverse model using neural networks based on expanded input space method
X Zhao, Y Tan - IEEE Transactions on Control Systems …, 2008 - ieeexplore.ieee.org
A neural network-based approach of identification for hysteresis and its inverse model is
proposed. In this method, a hysteretic operator is proposed to extract the change tendency of …
proposed. In this method, a hysteretic operator is proposed to extract the change tendency of …
An easy-to-implement hysteresis model identification method based on support vector regression
S Zhang, M Wang, P Zheng, G Qiao… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
The classical Preisach hysteresis model and its modifications are time consuming to
implement due to the determination of the weight function. Another defect of the Preisach …
implement due to the determination of the weight function. Another defect of the Preisach …