Well-posed model quality estimation by design of validation experiments

T.A.E. Oomen, O.H. Bosgra

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

21 Citations (Scopus)
3 Downloads (Pure)

Abstract

In deterministic model validation approaches, model errors can be attributed to both disturbances and model uncertainty, leading to an ill-posed problem formulation. The aim of this paper is to remedy the ill-posedness in model validation for robust control. A two-stage procedure is developed, where first an accurate, nonparametric, deterministic disturbance model is estimated from data, followed by the enforcement of averaging properties through an appropriate periodic experiment design. The proposed deterministic approach results in an asymptotically correctly estimated model uncertainty and is illustrated in a simulation example.
Original languageEnglish
Title of host publicationProceedings of the 15th IFAC Symposium on System Identification (SYSID 2009) 6-8 July 2009, Saint-Malo, France
EditorsE. Walter
Place of PublicationOxford
PublisherPergamon
Pages1199-1204
ISBN (Print)978-3-902661-47-0
Publication statusPublished - 2009

Fingerprint

Dive into the research topics of 'Well-posed model quality estimation by design of validation experiments'. Together they form a unique fingerprint.

Cite this