On least-squares identification of armax models

Wei Xing Zheng

doi:10.3182/20020721-6-es-1901.00476

On least-squares identification of armax models

Wei Xing Zheng

School of Computer, Data & Mathematical Sciences

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

13 Citations (Scopus)

Abstract

In this paper the problem of least-squares (LS) identification of ARMAX models is investigated from a new point of view. An efficient scheme for estimating the noise-induced bias in the LS parameter is in troduced by exploiting the unique structure of the ARMAX model and utilizing extra dela y edoutputs. Then a new type of LS based method is developed in combination with the bias correction technique. The proposed method makes no use of a prefilter and deals directly with the underlying ARMAX model. The important characteristics of the proposed method includes desired computational efficiency and superior estimation accuracy. The behavior of the proposed LS based method is also substantiated using simulation data while in comparison with other identification methods.

Original language	English
Title of host publication	IFAC Proceedings Volumes (IFAC-PapersOnline)
Editors	Gabriel Ferrate, Eduardo F. Camacho, Luis Basanez, Juan. A. de la Puente
Publisher	IFAC Secretariat
Pages	391-396
Number of pages	6
Edition	1
ISBN (Print)	9783902661746
DOIs	https://doi.org/10.3182/20020721-6-es-1901.00476
Publication status	Published - 2002
Event	15th World Congress of the International Federation of Automatic Control, 2002 - Barcelona, Spain Duration: 21 Jul 2002 → 26 Jul 2002

Publication series

Name	IFAC Proceedings Volumes (IFAC-PapersOnline)
Number	1
Volume	15
ISSN (Print)	1474-6670

Conference

Conference	15th World Congress of the International Federation of Automatic Control, 2002
Country/Territory	Spain
City	Barcelona
Period	21/07/02 → 26/07/02

Bibliographical note

Publisher Copyright:
Copyright © 2002 IFAC.

Keywords

ARMAX models
Least-squares method
Parameter estimation
System identification
Unbiased estimators

Access to Document

10.3182/20020721-6-es-1901.00476

Cite this

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title = "On least-squares identification of armax models",

abstract = "In this paper the problem of least-squares (LS) identification of ARMAX models is investigated from a new point of view. An efficient scheme for estimating the noise-induced bias in the LS parameter is in troduced by exploiting the unique structure of the ARMAX model and utilizing extra dela y edoutputs. Then a new type of LS based method is developed in combination with the bias correction technique. The proposed method makes no use of a prefilter and deals directly with the underlying ARMAX model. The important characteristics of the proposed method includes desired computational efficiency and superior estimation accuracy. The behavior of the proposed LS based method is also substantiated using simulation data while in comparison with other identification methods.",

keywords = "ARMAX models, Least-squares method, Parameter estimation, System identification, Unbiased estimators",

author = "Zheng, \{Wei Xing\}",

note = "Publisher Copyright: Copyright {\textcopyright} 2002 IFAC.; 15th World Congress of the International Federation of Automatic Control, 2002 ; Conference date: 21-07-2002 Through 26-07-2002",

year = "2002",

doi = "10.3182/20020721-6-es-1901.00476",

language = "English",

isbn = "9783902661746",

series = "IFAC Proceedings Volumes (IFAC-PapersOnline)",

publisher = "IFAC Secretariat",

number = "1",

pages = "391--396",

editor = "Gabriel Ferrate and Camacho, \{Eduardo F.\} and Luis Basanez and \{de la Puente\}, \{Juan. A.\}",

booktitle = "IFAC Proceedings Volumes (IFAC-PapersOnline)",

edition = "1",

}

Zheng, WX 2002, On least-squares identification of armax models. in G Ferrate, EF Camacho, L Basanez & JA de la Puente (eds), IFAC Proceedings Volumes (IFAC-PapersOnline). 1 edn, IFAC Proceedings Volumes (IFAC-PapersOnline), no. 1, vol. 15, IFAC Secretariat, pp. 391-396, 15th World Congress of the International Federation of Automatic Control, 2002, Barcelona, Spain, 21/07/02. https://doi.org/10.3182/20020721-6-es-1901.00476

On least-squares identification of armax models. / Zheng, Wei Xing.
IFAC Proceedings Volumes (IFAC-PapersOnline). ed. / Gabriel Ferrate; Eduardo F. Camacho; Luis Basanez; Juan. A. de la Puente. 1. ed. IFAC Secretariat, 2002. p. 391-396 (IFAC Proceedings Volumes (IFAC-PapersOnline); Vol. 15, No. 1).

Research output: Chapter in Book / Conference Paper › Conference Paper › peer-review

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KW - Parameter estimation

KW - System identification

KW - Unbiased estimators

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ER -

On least-squares identification of armax models

Abstract

Publication series

Conference

Bibliographical note

Keywords

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Cite this