This paper presents a method of the identification for the rate-dependent hysteresis in the
piezoelectric actuator (PEA) by use of neural networks. In this method, a special hysteretic …

A hybrid model is proposed in this paper to describe the static nonlinear and dynamic
characteristics of rate-dependent hysteresis in piezoelectric actuators. In this model, a neural …

Rate-dependent hysteresis nonlinearity in piezoelectric actuators severely limits micro-and
nanoscale system performance. It is necessary to establish a dynamic model to describe the …

For the application of neural networks to the approximation of hysteresis which is
characterized of multi-valued mapping and non-smooth nonlinearities, a novel modeling …

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 paper, a generalized hysteresis model is developed to describe both rate-
independent and rate-dependent hysteresis in piezoelectric actuators. Based on the …

A method for the identification of the rate-dependent hysteresis in piezoceramic actuators is
proposed. In this approach, both a so-called generalized gradient of the output with respect …

Hysteresis of piezoelectric actuators is rate-dependent at high frequencies, but most of the
hysteresis models are rate-independent and cannot describe the rate-dependent hysteresis …

In this paper, a novel rate-dependent Prandtl-Ishlinskii (PI) model is proposed to
characterize the rate-dependent hysteresis nonlinearity of piezoelectric actuators. The new …

A new polynomial fitting model based on a neural network is presented to characterize the
hysteresis in piezoelectric actuators. As hysteresis is multi-valued mapping, and traditional …