Fuzzy control for nonlinear uncertain electrohydraulic active suspensions with input constraint

Du, H; Zhang, N

Fuzzy control for nonlinear uncertain electrohydraulic active suspensions with input constraint

Du, H

Zhang, N

Permalink

Publication Type:: Journal Article
Citation:: IEEE Transactions on Fuzzy Systems, 2009, 17 (2), pp. 343 - 356
Issue Date:: 2009-05-13

Closed Access

	Filename	Description	Size
	2008007858OK.pdf		1.41 MB	Adobe PDF	View/Open

Copyright Clearance Process

Recently Added
In Progress
Closed Access

This item is closed access and not available.

Full metadata record

Field	Value	Language
dc.contributor.author	Du, H https://orcid.org/0000-0002-3439-3821	en_US
dc.contributor.author	Zhang, N https://orcid.org/0000-0001-6408-0044	en_US
dc.date.issued	2009-05-13	en_US
dc.identifier.citation	IEEE Transactions on Fuzzy Systems, 2009, 17 (2), pp. 343 - 356	en_US
dc.identifier.issn	1063-6706	en_US
dc.identifier.uri	http://hdl.handle.net/10453/9107
dc.description.abstract	This paper presents a Takagi-Sugeno (T-S) model-based fuzzy control design approach for electrohydraulic active vehicle suspensions considering nonlinear dynamics of the actuator, sprung mass variation, and constraints on the control input. The T-S fuzzy model is first applied to represent the nonlinear uncertain electrohydraulic suspension. Then, a fuzzy state feedback controller is designed for the obtained T-S fuzzy model with optimized H∞ performance for ride comfort by using the parallel-distributed compensation (PDC) scheme. The sufficient conditions for the existence of such a controller are derived in terms of linear matrix inequalities (LMIs). Numerical simulations on a full-car suspension model are performed to validate the effectiveness of the proposed approach. The obtained results show that the designed controller can achieve good suspension performance despite the existence of nonlinear actuator dynamics, sprung mass variation, and control input constraints. © 2009 IEEE.	en_US
dc.relation.ispartof	IEEE Transactions on Fuzzy Systems	en_US
dc.relation.isbasedon	10.1109/TFUZZ.2008.2011814	en_US
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Fuzzy control for nonlinear uncertain electrohydraulic active suspensions with input constraint	en_US
dc.type	Journal Article
utslib.citation.volume	2	en_US
utslib.citation.volume	17	en_US
utslib.for	0913 Mechanical Engineering	en_US
utslib.for	0102 Applied Mathematics	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
dc.location.activity	ISI:000265089700008	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 Mechanical and Mechatronic Engineering
utslib.copyright.status	closed_access
pubs.issue	2	en_US
pubs.publication-status	Published	en_US
pubs.volume	17	en_US

Abstract:

This paper presents a Takagi-Sugeno (T-S) model-based fuzzy control design approach for electrohydraulic active vehicle suspensions considering nonlinear dynamics of the actuator, sprung mass variation, and constraints on the control input. The T-S fuzzy model is first applied to represent the nonlinear uncertain electrohydraulic suspension. Then, a fuzzy state feedback controller is designed for the obtained T-S fuzzy model with optimized H∞ performance for ride comfort by using the parallel-distributed compensation (PDC) scheme. The sufficient conditions for the existence of such a controller are derived in terms of linear matrix inequalities (LMIs). Numerical simulations on a full-car suspension model are performed to validate the effectiveness of the proposed approach. The obtained results show that the designed controller can achieve good suspension performance despite the existence of nonlinear actuator dynamics, sprung mass variation, and control input constraints. © 2009 IEEE.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/9107