๐”– Bobbio Scriptorium
โœฆ   LIBER   โœฆ

Modeling of hysteresis in piezoelectric actuators using neural networks

โœ Scribed by Xinliang Zhang; Yonghong Tan; Miyong Su


Book ID
108299919
Publisher
Elsevier Science
Year
2009
Tongue
English
Weight
479 KB
Volume
23
Category
Article
ISSN
0888-3270

No coin nor oath required. For personal study only.


๐Ÿ“œ SIMILAR VOLUMES


Modeling hysteresis in piezoelectric act
โœ Liang Deng; Yonghong Tan ๐Ÿ“‚ Article ๐Ÿ“… 2009 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 663 KB

This paper presents a non-linear moving average model with exogenous inputs (NMAX) and a non-linear auto-regressive moving average model with exogenous inputs (NARMAX) respectively to model static and dynamic hysteresis inherent in piezoelectric actuators. The modeling approach is based on the expan

Modeling of rate-dependent hysteresis in
โœ GuoYing Gu; LiMin Zhu ๐Ÿ“‚ Article ๐Ÿ“… 2011 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 984 KB

In this paper, a new ellipse-like mathematic model is proposed to describe the rate-dependent hysteresis in piezoelectric actuators. Since the expressions of the model are completely analytical and can be determined only by a set of parameters, this method simplifies the modeling of complicated hyst

Diagonal recurrent neural network with m
โœ Liang Deng; Yonghong Tan ๐Ÿ“‚ Article ๐Ÿ“… 2008 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 990 KB

A novel neural network based method for modeling of rate-dependent hysteresis in piezoelectric actuators is proposed. In order to approximate the behavior of rate-dependent hysteresis which is a kind of nonsmooth dynamic nonlinearity with multi-valued mapping, a diagonal recurrent neural network (DR