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 …
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 …
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 …
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 …
Identification of piezoelectric hysteresis by a novel Duhem model based neural network
G Wang, G Chen - Sensors and Actuators A: Physical, 2017 - Elsevier
Duhem model has been widely used to describe the hysteresis property for many memory-
type nonlinear systems. In this paper, a novel parameter identification method based on …
type nonlinear systems. In this paper, a novel parameter identification method based on …
Intelligent modeling and control for nonlinear systems with rate-dependent hysteresis
JQ Mao, HS Ding - Science in China Series F: Information Sciences, 2009 - Springer
A new modeling approach for nonlinear systems with rate-dependent hysteresis is
proposed. The approach is used for the modeling of the giant magnetostrictive actuator …
proposed. The approach is used for the modeling of the giant magnetostrictive actuator …
Hybrid intelligent hysteresis model based on DBN-DNN algorithm and fusion Preisach operator
The hysteresis modeling of ferromagnetic materials in electrical equipment is one of the
basic theoretical studies in the field of electrical engineering. Long training time and poor …
basic theoretical studies in the field of electrical engineering. Long training time and poor …
Robust adaptive control of systems with hysteretic nonlinearities: a Duhem hysteresis modelling approach
Y Feng, CA Rabbath, T Chai, CY Su - AFRICON 2009, 2009 - ieeexplore.ieee.org
When the systems are preceded by unknown hysteresis nonlinearities, the system
performance will be degraded due to the existence of the unknown hysteresis. In order to …
performance will be degraded due to the existence of the unknown hysteresis. In order to …