Generation of initial estimates for Wiener-Hammerstein models via basis function expansions

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Abstract

Block-oriented models are often used to model nonlinear systems. They consist of linear dynamic (L) and nonlinear static (N) sub-blocks. This paper proposes a method to generate initial values for a Wiener-Hammerstein model (LNL cascade). The method starts from the best linear approximation (BLA) of the system, which provides an estimate of the product of the transfer functions of the two linear dynamic sub-blocks. Next, the poles of the BLA are assigned to both linear dynamic sub-blocks. The linear dynamics are then parameterized in terms of rational orthonormal basis functions, while the nonlinear sub-block is parameterized by a polynomial. This allows to reformulate the model to the cascade of a parallel Wiener (with parallel LN structure) and a linear dynamic system, which is bilinear in its parameters. After a bilinear optimization, the parallel Wiener part is projected to a single-branch Wiener model. The approach is illustrated on a simulation example.

Original languageEnglish
Pages (from-to)481-486
Number of pages6
JournalIFAC Proceedings Volumes
Volume47
Issue number3
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes
Event19th IFAC World Congress on International Federation of Automatic Control ( IFAC 2014) - Cape Town International Convention Centre, Cape Town, South Africa
Duration: 24 Aug 201429 Aug 2014
Conference number: 19
http://www.ifac2014.org

Keywords

  • Dynamic systems
  • Nonlinear systems
  • System identification
  • Wiener-Hammerstein model

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