Robust nonlinear H-infinity control of hyperbolic distributed parameter systems

Aggelogiannaki, E; Sarimveis, H

dc.contributor.author	Aggelogiannaki, E	en
dc.contributor.author	Sarimveis, H	en
dc.date.accessioned	2014-03-01T01:58:57Z
dc.date.available	2014-03-01T01:58:57Z
dc.date.issued	2009	en
dc.identifier.issn	0967-0661	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/28794
dc.subject	Hyperbolic distributed parameter systems	en
dc.subject	Radial basis function neural networks	en
dc.subject	H-infinity control	en
dc.subject	Robust control	en
dc.subject	Thermal systems	en
dc.subject.classification	Automation & Control Systems	en
dc.subject.classification	Engineering, Electrical & Electronic	en
dc.subject.other	MODEL-PREDICTIVE CONTROL	en
dc.subject.other	FEEDBACK-CONTROL	en
dc.subject.other	PDE SYSTEMS	en
dc.title	Robust nonlinear H-infinity control of hyperbolic distributed parameter systems	en
heal.type	journalArticle	en
heal.language	English	en
heal.publicationDate	2009	en
heal.abstract	A radial basis function (RBF) neural network model is developed for the identification of hyperbolic distributed parameter systems (DPSs). The empirical model is based only on process input-output data and is used for the estimation of the controlled variables at multiple spatial locations. The produced nonlinear model is transformed to a nonlinear state-space formulation, which in turn is used for deriving a robust H-infinity control law. The proposed methodology is applied to a long duct for the flow-based control of temperature distribution. The performance of the proposed method is illustrated by comparing it with conventional control strategies. (C) 2008 Elsevier Ltd. All rights reserved.	en
heal.publisher	PERGAMON-ELSEVIER SCIENCE LTD	en
heal.journalName	CONTROL ENGINEERING PRACTICE	en
dc.identifier.isi	ISI:000266300500010	en
dc.identifier.volume	17	en
dc.identifier.issue	6	en
dc.identifier.spage	723	en
dc.identifier.epage	732	en