Nonlinear and hysteretic modelling of magnetorheological elastomer base isolator using adaptive neuro-fuzzy inference system

Yu, Y; Li, Y; Li, J; Gu, X; Royel, S; Pokhrel, A

Nonlinear and hysteretic modelling of magnetorheological elastomer base isolator using adaptive neuro-fuzzy inference system

Yu, Y

Li, Y

Li, J

Gu, X

Royel, S

Pokhrel, A

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Publisher:: Trans Tech Publications
Publication Type:: Journal Article
Citation:: Applied Mechanics and Materials, 2016, 846 pp. 258 - 263 (6)
Issue Date:: 2016-07-25

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Field	Value	Language
dc.contributor.author	Yu, Y https://orcid.org/0000-0001-9592-8191	en_US
dc.contributor.author	Li, Y https://orcid.org/0000-0002-6720-8493	en_US
dc.contributor.author	Li, J https://orcid.org/0000-0002-2526-3048	en_US
dc.contributor.author	Gu, X https://orcid.org/0000-0003-3161-8391	en_US
dc.contributor.author	Royel, S https://orcid.org/0000-0001-6262-5282	en_US
dc.contributor.author	Pokhrel, A	en_US
dc.date.issued	2016-07-25	en_US
dc.identifier.citation	Applied Mechanics and Materials, 2016, 846 pp. 258 - 263 (6)	en_US
dc.identifier.issn	1660-9336	en_US
dc.identifier.uri	http://hdl.handle.net/10453/46903
dc.description.abstract	Magnetorheological elastomer (MRE) base isolator is a semi-active control device which has currently obtained increasing attention in the field of vibration control of civil structures. However, the inherent nonlinear and hysteretic response of the device is regarded as a challenge aspect for using the smart device to realize the high performance. Therefore, an accurate and robust model is essential to make full use of these unique features for its engineering applications. In this paper, to solve this issue, adaptive neuro-fuzzy inference system (ANFIS) is utilized to characterize the dynamic behavior of the device. In this proposed model, the inputs are historical displacements and applied current of the device while the output is the shear force generated. To validate its forecast performance, the ANFIS model is also compared with some conventional models. Finally, the result verifies that ANFIS has the best perfection ability among existing MRE-based device models.	en_US
dc.publisher	Trans Tech Publications	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP150102636
dc.relation.ispartof	Applied Mechanics and Materials	en_US
dc.relation.isbasedon	10.4028/www.scientific.net/AMM.846.258	en_US
dc.title	Nonlinear and hysteretic modelling of magnetorheological elastomer base isolator using adaptive neuro-fuzzy inference system	en_US
dc.type	Journal Article
utslib.citation.volume	846	en_US
utslib.for	0912 Materials Engineering	en_US
utslib.for	09 Engineering	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Civil and Environmental Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Computer Science
pubs.organisational-group	/University of Technology Sydney/Strength - CBI - Centre for Built Infrastructure
utslib.copyright.status	open_access
pubs.consider-herdc	true	en_US
pubs.publication-status	Published	en_US
pubs.volume	846	en_US

Abstract:

Magnetorheological elastomer (MRE) base isolator is a semi-active control device which has currently obtained increasing attention in the field of vibration control of civil structures. However, the inherent nonlinear and hysteretic response of the device is regarded as a challenge aspect for using the smart device to realize the high performance. Therefore, an accurate and robust model is essential to make full use of these unique features for its engineering applications. In this paper, to solve this issue, adaptive neuro-fuzzy inference system (ANFIS) is utilized to characterize the dynamic behavior of the device. In this proposed model, the inputs are historical displacements and applied current of the device while the output is the shear force generated. To validate its forecast performance, the ANFIS model is also compared with some conventional models. Finally, the result verifies that ANFIS has the best perfection ability among existing MRE-based device models.

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http://hdl.handle.net/10453/46903