Robust Stabilization of LPV Systems with Structured Uncertainty using Minimax Controllers

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dc.contributor.author Li, L
dc.contributor.author Ugrinovskii, VA
dc.contributor.editor NA
dc.date.accessioned 2012-02-02T11:09:54Z
dc.date.issued 2007-01
dc.identifier.citation Proceedings of the 46th IEEE Conference on Decision and Control, 2007, pp. 2767 - 2772
dc.identifier.isbn 978-1-4244-1497-0
dc.identifier.other E1UNSUBMIT en_US
dc.identifier.uri http://hdl.handle.net/10453/16512
dc.description.abstract This paper addresses a robust control scheduling scheme for uncertain linear parameter-varying systems with structured uncertainty. A gain-scheduled controller is proposed which employs a set of minimax optimal robust controllers and incorporates an interpolation rule to achieve continuity of the controller gain over a range of operating conditions. Novel weighted time-domain integral quadratic constraints are introduced to assist in the derivation of the controller. The key idea of the interpolation for the structured uncertainty case is to transform the parameterized algebraic Riccati inequalities into equivalent linear matrix inequalities. For every fixed value of the system parameter, the proposed controller guarantees robust stability and a certain bound on the worst-case performance of the corresponding uncertain closed loop system. Furthermore, a bound on the rate of parameter variations is obtained under which the closed loop LPV system is robustly stable. To obtain the proposed controller, a set of semi-definite programming problems are introduced; this enables an efficient numerical solution to the problem under consideration.
dc.publisher IEEE
dc.relation.hasversion Accepted manuscript version en_US
dc.relation.isbasedon 10.1109/CDC.2007.4434185
dc.title Robust Stabilization of LPV Systems with Structured Uncertainty using Minimax Controllers
dc.type Conference Proceeding
dc.parent Proceedings of the 46th IEEE Conference on Decision and Control
dc.journal.number en_US
dc.publocation United States en_US
dc.identifier.startpage 2767 en_US
dc.identifier.endpage 2772 en_US
dc.cauo.name FEIT.Faculty of Engineering & Information Technology en_US
dc.conference Verified OK en_US
dc.conference IEEE Conference on Decision and Control
dc.for 0906 Electrical and Electronic Engineering
dc.personcode 111645
dc.percentage 100 en_US
dc.classification.name Electrical and Electronic Engineering en_US
dc.classification.type FOR-08 en_US
dc.edition en_US
dc.custom IEEE Conference on Decision and Control en_US
dc.date.activity 20071212 en_US
dc.date.activity 2007-12-12
dc.location.activity New Orleans, LA en_US
dc.description.keywords Control systems , Interpolation , Linear matrix inequalities , Minimax techniques , Optimal control , Riccati equations , Robust control , Robust stability , Time domain analysis , Uncertainty en_US
dc.description.keywords Manifold learning
dc.description.keywords Least squares
dc.description.keywords Face recognition
dc.description.keywords Control systems , Interpolation , Linear matrix inequalities , Minimax techniques , Optimal control , Riccati equations , Robust control , Robust stability , Time domain analysis , Uncertainty
pubs.embargo.period Not known
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 Elec, Mech and Mechatronic Systems
utslib.copyright.status Open Access
utslib.copyright.date 2015-04-15 12:23:47.074767+10
utslib.collection.history General (ID: 2)


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