A fast nonlinear model identification method

The identification of nonlinear dynamic systems using linear-in-the-parameters models is studied. A fast recursive algorithm (FRA) is proposed to select both the model structure and to estimate the model parameters. Unlike orthogonal least squares (OLS) method, FRA solves the least-squares problem r...

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Veröffentlicht in:IEEE transactions on automatic control Jg. 50; H. 8; S. 1211 - 1216
Hauptverfasser: Kang Li, Jian-Xun Peng, Irwin, G.W.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.08.2005
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithm design and analysis
Applied sciences
Computational complexity
Computer science; control theory; systems
Control theory. Systems
Exact sciences and technology
fast recursive algorithm
Least squares methods
Matrix decomposition
Modelling and identification
Nonlinear dynamical systems
nonlinear system identification
Nonlinear systems
Numerical stability
Parameter estimation
System identification
US Department of Transportation
nonlinear system identification
Model matching
Identification
System identification
Dynamical system
Fast algorithm
Non linear system
Recursive algorithm
Computational complexity
fast recursive algorithm
Numerical stability
ISSN:0018-9286, 1558-2523
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:The identification of nonlinear dynamic systems using linear-in-the-parameters models is studied. A fast recursive algorithm (FRA) is proposed to select both the model structure and to estimate the model parameters. Unlike orthogonal least squares (OLS) method, FRA solves the least-squares problem recursively over the model order without requiring matrix decomposition. The computational complexity of both algorithms is analyzed, along with their numerical stability. The new method is shown to require much less computational effort and is also numerically more stable than OLS.
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ISSN:0018-9286
1558-2523
DOI:10.1109/TAC.2005.852557