Identification of non-linear system structure and parameters using regime decomposition

An off-line algorithm for empirical modeling and identification of non-linear dynamic systems is presented. The minimal input to the algorithm is a sequence of empirical data and the model order. Using this information, the algorithm searches for an optimal model structure and parameters within a ri...

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Bibliographic Details
Published inAutomatica (Oxford) Vol. 31; no. 2; pp. 321 - 326
Main Authors Johansen, Tor A., Foss, Bjarne A.
Format Journal Article
LanguageEnglish
Published Oxford Elsevier Ltd 01.02.1995
Elsevier
Subjects
Applied sciences
Computer science; control theory; systems
Control theory. Systems
Exact sciences and technology
fermentation processes
modeling
Modelling and identification
Non-linear systems
process models
system identification
process models
fermentation processes
modeling
system identification
Non-linear systems
Parameter estimation
Heuristic method
Decomposition
Identification
Non linear system
Algorithm
Modeling
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Summary:An off-line algorithm for empirical modeling and identification of non-linear dynamic systems is presented. The minimal input to the algorithm is a sequence of empirical data and the model order. Using this information, the algorithm searches for an optimal model structure and parameters within a rich non-linear model set. The model representation is based on the interpolation of a number of simple local models, where each local model has a limited range of validity, but the local models yield a complete global model when interpolated. The method is illustrated using simulated data.
ISSN:0005-1098
1873-2836
DOI:10.1016/0005-1098(94)00096-2