Nonlinear functional characterizations of uncertainty in model validation

  • Roy Smith
  • , Geir Dullerud

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Model validation provides a useful means of assessing the ability of a model to account for a specific experimental observation, and has application to modeling, identification and fault detection. In this paper we consider a new approach to the linear fractional transformation (LFT) model validation problem by deploying quadratic functionals, and more generally nonlinear functionals, to specify noise and dynamical perturbation sets. Sufficient conditions for invalidation of such models are provided in terms of semidefinite programming problems.

Original languageEnglish (US)
Title of host publicationIFAC Proceedings Volumes (IFAC-PapersOnline)
EditorsGabriel Ferrate, Eduardo F. Camacho, Luis Basanez, Juan. A. de la Puente
PublisherIFAC Secretariat
Pages151-156
Number of pages6
Edition1
ISBN (Print)9783902661746
DOIs
StatePublished - 2002
Event15th World Congress of the International Federation of Automatic Control, 2002 - Barcelona, Spain
Duration: Jul 21 2002Jul 26 2002

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Number1
Volume15
ISSN (Print)1474-6670

Other

Other15th World Congress of the International Federation of Automatic Control, 2002
Country/TerritorySpain
CityBarcelona
Period7/21/027/26/02

Keywords

  • Model validation
  • Nonlinear functionals
  • Semidefinite programming

ASJC Scopus subject areas

  • Control and Systems Engineering

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