Identification of Piecewise Affine Wiener Systems Using Data Partition
2003 (English)Report (Other academic)
The aim of the given paper is the development of an approach for the identification of affine Wiener systems with piecewise linear nonlinearities, i.e. when the linear part with unknown parameters is followed by a saturation-like function with unknown slopes. It is shown here that by a simple data rearrangement and by a following data partition the problem of identification of the nonlinear Wiener system could be reduced to a linear parametric estimation problem. Afterwards, estimates of the unknown parameters of linear regression models are obtained by processing respective sets of input-output data. A technique based on ordinary least squares, to be used in a case of missing data, and on the expectation-maximization algorithm is proposed here for the identification of parameters of linear and nonlinear parts of the Wiener system, including the unknown threshold of the piecewise nonlinearity, too. The results of numerical simulation and identification obtained by processing observations of input-output signals of distinct discrete-time Wiener systems with two types piecewise nonlinearities by computer are given.
Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2003. , 38 p.
LiTH-ISY-R, ISSN 1400-3902 ; 2523
System identification, Parameter estimation, Nonlinear systems, Wiener systems
IdentifiersURN: urn:nbn:se:liu:diva-55810ISRN: LiTH-ISY-R-2523OAI: oai:DiVA.org:liu-55810DiVA: diva2:316522