[article] 
inIndustrial & engineering chemistry research > Vol. 47 N°17 (Septembre 2008) . - p. 6640–6647

Titre :	Nonparametric identification for control of MIMO hammerstein systems
Type de document :	texte imprimé
Auteurs :	Jyh-Cheng Jeng, Auteur ; Hsiao-Ping Huang, Auteur
Année de publication :	2008
Article en page(s) :	p. 6640–6647
Note générale :	Chemical engineering
Langues :	Anglais (eng)
Mots-clés :	Hammerstein models Nonparametric method Linear dynamic subsystem Algebraic nonlinear function
Résumé :	A new nonparametric method to identify multivariable Hammerstein models is presented. The Hammerstein model is characterized by a combination of a linear dynamic subsystem and an algebraic nonlinear function. There could be many different models that give the same input−output realization. The purpose of this identification is to find out one among those models for controller design. This identification uses a sequence of specially designed test signals for excitation. The linear dynamic subsystem is identified as a finite sequence of impulse response (FIR), and the static nonlinearity is identified as a multi-input−multi-output (MIMO) functional mapping. By making use of this special test signal, the FIR sequence can be estimated under a single-input−single-output (SISO) framework. Moreover, the identification for linear subsystem can be decoupled from that for the nonlinear static part. This nonparametric model can be used for model predictive control applications.
En ligne :	http://pubs.acs.org/doi/abs/10.1021/ie071512q

[article] Nonparametric identification for control of MIMO hammerstein systems [texte imprimé] / Jyh-Cheng Jeng, Auteur ; Hsiao-Ping Huang, Auteur . - 2008 . - p. 6640–6647.
Chemical engineering
Langues : Anglais (eng)
in Industrial & engineering chemistry research > Vol. 47 N°17 (Septembre 2008) . - p. 6640–6647

Mots-clés :	Hammerstein models Nonparametric method Linear dynamic subsystem Algebraic nonlinear function
Résumé :	A new nonparametric method to identify multivariable Hammerstein models is presented. The Hammerstein model is characterized by a combination of a linear dynamic subsystem and an algebraic nonlinear function. There could be many different models that give the same input−output realization. The purpose of this identification is to find out one among those models for controller design. This identification uses a sequence of specially designed test signals for excitation. The linear dynamic subsystem is identified as a finite sequence of impulse response (FIR), and the static nonlinearity is identified as a multi-input−multi-output (MIMO) functional mapping. By making use of this special test signal, the FIR sequence can be estimated under a single-input−single-output (SISO) framework. Moreover, the identification for linear subsystem can be decoupled from that for the nonlinear static part. This nonparametric model can be used for model predictive control applications.
En ligne :	http://pubs.acs.org/doi/abs/10.1021/ie071512q