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 …
3D InspectionNet: a deep 3D convolutional neural networks based approach for 3D defect detection on concrete columns
Deep learning-based defect feature recognition from 2D image datasets, has recently been
a very active research area and deep Convolutional Neural Networks have brought …
a very active research area and deep Convolutional Neural Networks have brought …
Adaptive inverse control of piezoelectric actuators based on segment similarity
X Liu, M Huang, R Xiong, J Shan… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
The hysteresis behavior of piezoelectric actuators is primarily responsible for the decrease
of the precision and performance of the nanopositioning systems. To compensate for …
of the precision and performance of the nanopositioning systems. To compensate for …
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 …
An Extreme Learning Machine for the Simulation of Different Hysteretic Behaviors
Hysteresis is a non− unique phenomenon known as a multi− valued mapping in different
fields of science and engineering. Accurate identification of the hysteretic systems is a …
fields of science and engineering. Accurate identification of the hysteretic systems is a …
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 …
Identification of the stick and slip motion between contact surfaces using artificial neural networks
The paper presents work related to nonlinear system parameters identification. The research
is focused on systems with hysteretic stiffness characteristics. The identification procedure is …
is focused on systems with hysteretic stiffness characteristics. The identification procedure is …
Seismic vibration control of 3D steel frames with irregular plans using eccentrically placed MR dampers
Y Hu, L Liu, S Rahimi - Sustainability, 2017 - mdpi.com
There has been a significant increase in attention toward designing smart structures and
vibration control of structures in recent decades, and numerous methods and algorithms …
vibration control of structures in recent decades, and numerous methods and algorithms …
A fast and accurate piezoelectric actuator modeling method based on truncated least squares support vector regression
In order to improve the applicability of piezoelectric actuators (PEAs) in precision
positioning, least squares support vector regression (LS-SVR) is applied to model hysteresis …
positioning, least squares support vector regression (LS-SVR) is applied to model hysteresis …
Temperature dependent hysteresis modeling of a piezotube actuator using elman neural network
M Al Janaideh, M Al Saaideh… - Dynamic Systems …, 2019 - asmedigitalcollection.asme.org
In this study, the hysteresis nonlinearities of a piezotube actuator are investigated under
different levels of surrounding temperature. The experimental results show that increasing of …
different levels of surrounding temperature. The experimental results show that increasing of …