Identification of time-varying Hammerstein systems from ensemble data

In this paper, we describe a new technique to identify rapidly time-varying Hammerstein systems from ensembles of input-output realizations. The technique involves two steps. A correlation approach is first used to obtain initial estimates of the linear subsystem parameters for every sampling time....

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Bibliographic Details
Published inAnnals of biomedical engineering Vol. 29; no. 7; pp. 619 - 635
Main Authors Lortie, M, Kearney, R E
Format Journal Article
LanguageEnglish
Published United States Springer Nature B.V 01.07.2001
Subjects
Algorithms
Analysis of Variance
Biomedical Engineering
Cascade control systems
Computer simulation
Identification (control systems)
Iterative methods
Linear Models
Mathematical models
Models, Biological
Nonlinear Dynamics
Optimization algorithms
Studies
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Summary:In this paper, we describe a new technique to identify rapidly time-varying Hammerstein systems from ensembles of input-output realizations. The technique involves two steps. A correlation approach is first used to obtain initial estimates of the linear subsystem parameters for every sampling time. An iterative optimization algorithm is then employed to produce final estimates of the system parameters. The input does not need to be white. The technique was tested on simulated data and was found to produce excellent results under realistic conditions.
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ISSN:0090-6964
1573-9686
DOI:10.1114/1.1380421