Modeling hysteresis using hybrid method of continuous transformation and neural networks
Z Tong, Y Tan, X Zeng - Sensors and Actuators A: Physical, 2005 - Elsevier
A novel and simple approach to modeling hysteresis nonlinearities is proposed. The
continuous transformation technique is used to construct an elementary hysteresis model …
continuous transformation technique is used to construct an elementary hysteresis model …
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 …
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 …
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 …
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 …
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 …
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 …
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 …
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 modeling based on the hysteretic chaotic neural network
X Liu, C Xiu - Neural Computing and Applications, 2008 - Springer
The hysteresis activation function is proposed, and a novel hysteretic chaotic neuron model
is constructed by the function. It is shown that the model may exhibit a complex dynamic …
is constructed by the function. It is shown that the model may exhibit a complex dynamic …