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 …

This paper presents a neural network (NN) based model for hysteresis nonlinearity with
multivalued mapping. It is proved that the Preisach-type hysteresis can be transformed into a …

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 …

This paper presents a hybrid neural network (NN) model for hysteresis in mechanical or
piezoelectric systems. It is proven that the Preisach-type hysteresis can be transformed to …

In this paper, a new hysteretic operator (HO) for hysteresis in piezoelectric actuators is
proposed. Based on the constructed HO, the input space of neural networks is expanded …

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 …

A novel and simple approach to modeling hysteresis nonlinearities is proposed. The
continuous transformation technique is used to construct an elementary hysteresis model …

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 …

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 …

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 …