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DOKOUPIL, J. PIVOŇKA, P.
Original Title
A Levenberg-Marquardt algorithm with instrumental variables and its application on the identification of dynamic system
Type
conference paper
Language
English
Original Abstract
This article deals with process identification, using nonlinear ARX model via feed-forward multilayer neural network. Estimation of network parameters is achieved using the Levenberg-Marquardt (LM) method in iterative batch mode adaptation. In order to obtain consistent estimate, original implementations of LM algorithm - which include instrumental variables (IV) technique - are suggested. Basic and extended IV methods are presented as some of the IV methods. Advantages of the proposed approach are illustrated in the example simulations on the real process, using B&R PLC.
Keywords
Neural networks, Levenberg-Marquardt, NARX, Instrumental variables, System identification
Authors
DOKOUPIL, J.; PIVOŇKA, P.
RIV year
2010
Released
20. 10. 2010
Publisher
DAAAM International Vienna
Location
TU Wien Karlsplatz 13/311 A-1040 Vienna Austria
ISBN
978-3-901509-73-5
Book
Annals of DAAAM for 2010 & Proceedings of the 21st International DAAAM Symposium, No1
Edition
Edition number
1
Pages from
1359
Pages to
1360
Pages count
2
BibTex
@inproceedings{BUT35747, author="Jakub {Dokoupil} and Petr {Pivoňka}", title="A Levenberg-Marquardt algorithm with instrumental variables and its application on the identification of dynamic system", booktitle="Annals of DAAAM for 2010 & Proceedings of the 21st International DAAAM Symposium, No1", year="2010", series="2010", number="1", pages="1359--1360", publisher="DAAAM International Vienna", address="TU Wien Karlsplatz 13/311 A-1040 Vienna Austria", isbn="978-3-901509-73-5" }