Handling Certain Structure Information in Subspace Identification
2009 (English)In: Proceedings of the 15th IFAC Symposium on System Identification, 2009, 90-95 p.Conference paper (Refereed)
The prediction-error approach to parameter estimation of linear models often involves solving a non-convex optimization problem. In some cases, it is therefore difficult to guarantee that the global optimum will be found. A common way to handle this problem is to find an initial estimate, hopefully lying in the region of attraction of the global optimum, using some other method. The prediction-error estimate can then be obtained by a local search starting at the initial estimate. In this paper, a new approach for finding an initial estimate of certain linear models utilizing structure and the subspace method is presented. The polynomial models are first written on the observer canonical state-space form, where the specific structure is later utilized, rendering least-squares estimation problems with linear equality constraints.
Place, publisher, year, edition, pages
2009. 90-95 p.
, IFAC-PapersOnLine, ISSN 2405-8963 ; 42(10)
System identification, Subspace methods, Black-box models
Engineering and Technology Control Engineering
IdentifiersURN: urn:nbn:se:liu:diva-45374DOI: 10.3182/20090706-3-FR-2004.00014Local ID: 82291OAI: oai:DiVA.org:liu-45374DiVA: diva2:266236
15th IFAC Symposium on System Identification, Saint-Malo, France, July, 2009