Combining the best linear approximation and dimension reduction to identify thelinear blocks of parallel Wiener systems
2012 (English)Report (Other academic)
A Wiener model is a fairly simple, well known, and often used nonlinearblock-oriented black-box model. A possible generalization of the class ofWiener models lies in the parallel Wiener model class. This paper presents amethod to estimate the linear time-invariant blocks of such parallel Wienermodels from input/output data only. The proposed estimation methodcombines the knowledge obtained by estimating the best linear approxima-tion of a nonlinear system with a dimension reduction method to estimatethe linear time-invariant blocks present in the model. The estimation of thestatic nonlinearity is fairly easy once the linear blocks are known.
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2012. , 15 p.
LiTH-ISY-R, ISSN 1400-3902 ; 3050
System identification, Wiener systems, Best linear approximation, Dimension reduction
IdentifiersURN: urn:nbn:se:liu:diva-84517ISRN: LiTH-ISY-R-3050OAI: oai:DiVA.org:liu-84517DiVA: diva2:559973