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Improved Initialization for Nonlinear State-Space Modeling

Anna Marconato ; Jonas Sjöberg (Institutionen för signaler och system, Mekatronik) ; Johan Suykens ; Johan Schoukens
IEEE Transactions on Instrumentation and Measurement (0018-9456). Vol. 63 (2014), 4, p. 972-980.
[Artikel, refereegranskad vetenskaplig]

This paper discusses a novel initialization algorithm for the estimation of nonlinear state-space models. Good initial values for the model parameters are obtained by identifying separately the linear dynamics and the nonlinear terms in the model. In particular, the nonlinear dynamic problem is transformed into an approximate static formulation, and simple regression methods are applied to obtain the solution in a fast and efficient way. The proposed method is validated by means of two measurement examples: the Wiener-Hammerstein benchmark problem, and the identification of a crystal detector.

Nyckelord: Multilayer perceptrons; nonlinear dynamical systems; nonlinear modeling; state-space models; system identification

Denna post skapades 2014-04-04. Senast ändrad 2017-06-28.
CPL Pubid: 196291


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Institutioner (Chalmers)

Institutionen för signaler och system, Mekatronik (2005-2017)



Chalmers infrastruktur