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Initialization of nonlinear state-space models applied to the Wiener–Hammerstein benchmark

Anna Marconato ; Jonas Sjöberg (Institutionen för signaler och system, Mekatronik) ; Johan Schoukens
Control Engineering Practice (0967-0661). Vol. 20 (2012), 11, p. 1126–1132.
[Artikel, refereegranskad vetenskaplig]

In this work a new initialization scheme for nonlinear state-space models is applied to the problem of identifying a Wiener–Hammerstein system on the basis of a set of real data. The proposed approach combines ideas from the statistical learning community with classic system identification methods. The results on the benchmark data are discussed and compared to the ones obtained by other related methods.

Nyckelord: System identification, Nonlinear models, Wiener–Hammerstein benchmark data, State-space models, Neural networks



Denna post skapades 2012-09-27. Senast ändrad 2014-10-07.
CPL Pubid: 164073

 

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Institutioner (Chalmers)

Institutionen för signaler och system, Mekatronik

Ämnesområden

Reglerteknik
Signalbehandling

Chalmers infrastruktur