DSpace - Tor Vergata >
Facoltà di Ingegneria >
Tesi di dottorato in ingegneria >

Please use this identifier to cite or link to this item: http://hdl.handle.net/2108/596

Full metadata record

DC FieldValueLanguage
contributor.advisorTornambè, Antonio-
contributor.advisorAbdallah, Chaovki T.-
contributor.authorArgento, Claudio-
date.accessioned2008-08-29T09:29:00Z-
date.available2008-08-29T09:29:00Z-
date.issued2008-08-29T09:29:00Z-
identifier.urihttp://hdl.handle.net/2108/596-
description19. cicloen
description.abstractThe introduction provides an overview on complex networks, trying to investigate what apparently different kinds of networks have in common. Some statistical properties are illustrated and a simulation tool for the analysis of complex networks is presented. A weighted directed random graph is used as network model. The graph contains a fixed number N of nodes and a variable number of edges: in particular, each edge is present with probability p. Some statistical properties (such as strong connection, global and local efficiency, cost, etc) are computed and their reliance on probability p is studied. Some probability distributions (such as shortest path, edge/node load) are also drawn and, by using the method of stages, the best fitting curves are computed. The way as parameters characterizing such curves change when p varies is also investigated. The general structure of the proposed fitting technique allows to model several aspects of complex networks and makes possible its use in many different fields. Finally, the tracking control problem of linear time invariant (LTI) systems when the plant and the controller belong to the same network is considered. Time delays can degrade significantly the performance of a networked control system, eventually leading to instability. The problem characterized by constant and known network delays is analytically examined, showing how to construct a plant state predictor in order to compensate the time delays between the plant and the controller, so to allow the tracking of a reference signal. Computer simulations illustrate the effectiveness of the proposed technique, also when time delays slightly vary around a mean value.en
format.extent5703529 bytes-
format.mimetypeapplication/pdf-
language.isoenen
subjectcomplex networksen
subjectidentificationen
subjectmethod of stagesen
subjectcurve fittingen
subjectnetworked control systemsen
subjecttracking controlen
subjectdelay compensationen
subject.classificationING-INF/04 Automaticaen
titleComplex networks: analysis and controlen
typeDoctoral thesisen
degree.nameDottorato in informatica e ingegneria dell'automazioneen
degree.levelDottoratoen
degree.disciplineFacoltà di ingegneriaen
degree.grantorUniversità degli studi di Roma Tor Vergataen
date.dateofdefenseA.A. 2006/2007en
Appears in Collections:Tesi di dottorato in ingegneria

Files in This Item:

File Description SizeFormat
tesi.pdf5569KbAdobe PDFView/Open

Show simple item record

All items in DSpace are protected by copyright, with all rights reserved.