Treffer: A fast nonlinear model identification method
Title:
A fast nonlinear model identification method
Authors:
Source:
IEEE transactions on automatic control. 50(8):1211-1216
Publisher Information:
New York, NY: Institute of Electrical and Electronics Engineers, 2005.
Publication Year:
2005
Physical Description:
print, 10 ref
Original Material:
INIST-CNRS
Subject Terms:
Control theory, operational research, Automatique, recherche opérationnelle, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Automatique théorique. Systèmes, Control theory. Systems, Modélisation et identification, Modelling and identification, Ajustement modèle, Model matching, Ajustamiento modelo, Algorithme rapide, Fast algorithm, Algoritmo rápido, Algorithme récursif, Recursive algorithm, Algoritmo recursivo, Complexité calcul, Computational complexity, Complejidad computación, Identification système, System identification, Identificación sistema, Identification, Identificación, Stabilité numérique, Numerical stability, Estabilidad numérica, Système dynamique, Dynamical system, Sistema dinámico, Système non linéaire, Non linear system, Sistema no lineal, fast recursive algorithm, nonlinear system identification, numerical stability
Document Type:
Fachzeitschrift
Article
File Description:
text
Language:
English
Author Affiliations:
School of Electrical and Electronic Engineering, Queen's University of Belfast, Belfast BT9 5AH, United Kingdom
ISSN:
0018-9286
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.16995821
Database:
PASCAL Archive
Weitere Informationen
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.