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**Harvard**

Sjöberg, J., Lieve, L. och Schoukens, J. (2012) *Identification of Wiener–Hammerstein models: Two algorithms based on the best split of a linear model applied to the SYSID'09 benchmark problem*.

** BibTeX **

@article{

Sjöberg2012,

author={Sjöberg, Jonas and Lieve, Lauwers and Schoukens, Johan},

title={Identification of Wiener–Hammerstein models: Two algorithms based on the best split of a linear model applied to the SYSID'09 benchmark problem},

journal={Control Engineering Practice},

issn={0967-0661},

volume={20},

issue={11},

pages={1119–1125},

abstract={This paper describes the identification of Wiener–Hammerstein models and two recently suggested algorithms are applied to the SYSID'09 benchmark data. The most difficult step in the identification process of such block-oriented models is to generate good initial values for the linear dynamic blocks so that local minima are avoided. Both of the considered algorithms obtain good initial estimates by using the best linear approximation (BLA) which can easily be estimated from data. Given the BLA, the two algorithms differ in the way the dynamics are separated into two linear parts. The first algorithm simply considers all possible splits of the dynamics. Each of the splits is used to initialize one Wiener–Hammerstein model using linear least-squares and the best performing model is selected. In the second algorithm, both linear blocks are initialized with the entire BLA model using basis function expansions of the poles and zeros of the BLA. This gives over-parameterized linear blocks and their order is decreased in a model reduction step. Both algorithms are explained and their properties are discussed. They both give good, comparable models on the benchmark data.},

year={2012},

keywords={Wiener–Hammerstein systems, Hammerstein systems, Wiener systems, Nonlinear system identification, Initial estimates, Best linear approximation},

}

** RefWorks **

RT Journal Article

SR Electronic

ID 164072

A1 Sjöberg, Jonas

A1 Lieve, Lauwers

A1 Schoukens, Johan

T1 Identification of Wiener–Hammerstein models: Two algorithms based on the best split of a linear model applied to the SYSID'09 benchmark problem

YR 2012

JF Control Engineering Practice

SN 0967-0661

VO 20

IS 11

AB This paper describes the identification of Wiener–Hammerstein models and two recently suggested algorithms are applied to the SYSID'09 benchmark data. The most difficult step in the identification process of such block-oriented models is to generate good initial values for the linear dynamic blocks so that local minima are avoided. Both of the considered algorithms obtain good initial estimates by using the best linear approximation (BLA) which can easily be estimated from data. Given the BLA, the two algorithms differ in the way the dynamics are separated into two linear parts. The first algorithm simply considers all possible splits of the dynamics. Each of the splits is used to initialize one Wiener–Hammerstein model using linear least-squares and the best performing model is selected. In the second algorithm, both linear blocks are initialized with the entire BLA model using basis function expansions of the poles and zeros of the BLA. This gives over-parameterized linear blocks and their order is decreased in a model reduction step. Both algorithms are explained and their properties are discussed. They both give good, comparable models on the benchmark data.

LA eng

DO 10.1016/j.conengprac.2012.07.001

LK http://dx.doi.org/10.1016/j.conengprac.2012.07.001

LK http://publications.lib.chalmers.se/records/fulltext/164072/local_164072.pdf

OL 30