@inproceedings{2219a2c48013463aa800909b0126c7ba,
title = "Modeling rate-dependent and thermal-drift hysteresis through preisach model and neural network optimization approach",
abstract = "Smart material actuators like Piezoelectric(PZT) are widely used in Micro/Nano manipulators, but their hysteresis behaviors are complex and difficult to model. Most hysteresis models are based on elementary quasistatic operators and are not suitable for modeling rate-dependent or thermal-drift behaviors of the actuators. This work proposes a Preisach model based neurodynamic optimization model to account for the complex hysteresis behaviors of the smart material actuator system. Through simulation study, the rate-dependent and the thermal-drift behaviors are simulated via Bouc-Wen model. The μ-density function of the Preisach model is identified on-line through neurodynamic optimization method to suit for the varied rate of the input signals. The output of the actuator system is predicated in realtime based on the on-line identified μ-density plane. It is shown experimentally that the predicated hysteresis loops match the simulated PZT loops very well.",
keywords = "Bouc-Wen Model, Hysteresis, Neurodynamic optimization, Preisach Model",
author = "Shunli Xiao and Yangmin Li",
year = "2012",
month = aug,
day = "23",
doi = "10.1007/978-3-642-31346-2_21",
language = "English",
isbn = "9783642313455",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
number = "PART 1",
pages = "179--187",
booktitle = "Advances in Neural Networks, ISNN 2012 - 9th International Symposium on Neural Networks, Proceedings",
edition = "PART 1",
note = "9th International Symposium on Neural Networks, ISNN 2012 ; Conference date: 11-07-2012 Through 14-07-2012",
}