CCE Faculty Articles
Identification of Nonlinear Systems Using a B-Splines Parametric Subspace Approach
Document Type
Article
Publication Title
Proceedings of the American Control Conference
Event Date/Location
San Diego, CA
ISSN
0743-1619
Publication Date
6-1999
Abstract
System identification theory has benefited from developments in numerical linear algebra, in particular, generalizations and extensions of the singular value decomposition. Thanks to these new developments, a new class of algorithms collectively known as subspace algorithms has emerged. These algorithms have the advantage of working directly in the state-space domain, which makes them quite appealing for designing model-based controllers. Extensions to nonlinear systems have appeared for bilinear and Hammerstein systems. We introduce a B-splines subspace approach for identifying nonlinear systems. It is based on a parametric B-splines transformation of the inputs, followed by linear system identification. In this sense, our approach identifies a Hammerstein model with B-splines as the input basis. Since the inputs depend parametrically on the spline functions, an iterative procedure is developed for obtaining the optimal parameters. An example of a rainfall-runoff application is presented.
DOI
10.1109/ACC.1999.786259
First Page
3955
Last Page
3959
NSUWorks Citation
Ramos, Jose A. and Durand, J. F., "Identification of Nonlinear Systems Using a B-Splines Parametric Subspace Approach" (1999). CCE Faculty Articles. 389.
https://nsuworks.nova.edu/gscis_facarticles/389
