Identification of Hammerstein–Wiener models

Identification of Hammerstein–Wiener models

This paper develops and illustrates a new maximum-likelihood based method for the identification of Hammerstein–Wiener model structures. A central aspect is that a very general situation is considered wherein multivariable data, non-invertible Hammerstein and Wiener nonlinearities, and colored stoch...

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Veröffentlicht in:Automatica (Oxford) 2013-01, Vol.49 (1), p.70-81
Hauptverfasser: Wills, Adrian, Schön, Thomas B., Ljung, Lennart, Ninness, Brett
Format: Artikel
Sprache:eng
Schlagworte:
Applied sciences
Automatic control
Block-oriented models
Computer science
control theory
systems
Control theory. Systems
Dynamic systems
Exact sciences and technology
Expectation maximization algorithm
Hammerstein
Information technology
Informationsteknik
Maximum Likelihood
Modelling and identification
Monte Carlo method
Nonlinear models
Particle methods
Reglerteknik
Smoothing
System identification
System theory
TECHNOLOGY
TEKNIKVETENSKAP
Wiener
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Beschreibung
Zusammenfassung:This paper develops and illustrates a new maximum-likelihood based method for the identification of Hammerstein–Wiener model structures. A central aspect is that a very general situation is considered wherein multivariable data, non-invertible Hammerstein and Wiener nonlinearities, and colored stochastic disturbances both before and after the Wiener nonlinearity are all catered for. The method developed here addresses the blind Wiener estimation problem as a special case.
ISSN:0005-1098
1873-2836
1873-2836
DOI:10.1016/j.automatica.2012.09.018