Efficient Parameterization for Grey-box Model Identification of Complex Physical Systems

Mogens Blanke, Morten Knudsen

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Grey box model identification preserves known physical structures in a model but with limits to the possible excitation, all parameters are rarely identifiable, and different parametrizations give significantly different model quality. Convenient methods to show which parameterizations are the better would be very useful. This paper shows how we can assess the parameter interdependence and model quality. Hessian matrix decomposition is employed to show linear dependencies between variables and to put a quality tag on different parameterizations. The method determines parameter relations that need be constrained to achieve satisfactory convergence. Identification of nonlinear models for a ship illustrate the concept.
Original languageEnglish
Title of host publicationProceedings 14. IFAC Symposium on System Identification SYSID'2006
PublisherInternational Federation of Automatic Control
Publication date2006
DOIs
Publication statusPublished - 2006
Event14th IFAC Symposium on System Identification (SYSID 2006) - Newcastle, Australia
Duration: 1 Jan 2006 → …
Conference number: 14

Conference

Conference14th IFAC Symposium on System Identification (SYSID 2006)
Number14
CountryAustralia
CityNewcastle
Period01/01/2006 → …

Keywords

  • Grey-box identication
  • Parameter inter-depence
  • Factor analysis
  • Marine systems

Cite this

Blanke, M., & Knudsen, M. (2006). Efficient Parameterization for Grey-box Model Identification of Complex Physical Systems. In Proceedings 14. IFAC Symposium on System Identification SYSID'2006 International Federation of Automatic Control. https://doi.org/10.3182/20060329-3-AU-2901.00049