NDLI: A new kernel-based approach to overparameterized Hammerstein system identification

Content Provider	IEEE Xplore Digital Library
Author	Risuleo, Riccardo S. Bottegal, Giulio Hjalmarsson, Hakan
Copyright Year	2015
Description	Author affiliation: ACCESS Linnaeus Center, School of Electrical Engineering, KTH Royal Institute of Technology, Sweden (Risuleo, Riccardo S.; Bottegal, Giulio; Hjalmarsson, Hakan)
Abstract	The object of this paper is the identification of Hammerstein systems, which are dynamic systems consisting of a static nonlinearity and a linear time-invariant dynamic system in cascade. We assume that the nonlinear function can be described as a linear combination of p basis functions. We model the system dynamics by means of an np-dimensional vector. This vector, usually referred to as overparameterized vector, contains all the combinations between the nonlinearity coefficients and the first n samples of the impulse response of the linear block. The estimation of the overparameterized vector is performed with a new regularized kernel-based approach. To this end, we introduce a novel kernel tailored for overparameterized models, which yields estimates that can be uniquely decomposed as the combination of an impulse response and p coefficients of the static nonlinearity. As part of the work, we establish a clear connection between the proposed identification scheme and our recently developed nonparametric method based on the stable spline kernel.
Starting Page	115
Ending Page	120
File Size	291448
Page Count	6
File Format	PDF
e-ISBN	9781479978861
DOI	10.1109/CDC.2015.7402095
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-12-15
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Kernel Linear systems Splines (mathematics) Nonlinear dynamical systems System dynamics Finite impulse response filters Covariance matrices
Content Type	Text
Resource Type	Article

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