Two-stage Recursive Least Squares Parameter Estimation Algorithm for Multivariate Output-error Autoregressive Moving Average Systems

Yunze Guo; Lijuan Wan; Ling Xu; Feng Ding; Ahmed Alsaedi; Tasawar Hayat

doi:10.1007/s12555-018-0512-0

Two-stage Recursive Least Squares Parameter Estimation Algorithm for Multivariate Output-error Autoregressive Moving Average Systems

Yunze Guo
, Lijuan Wan
, Ling Xu
, Feng Ding
, Ahmed Alsaedi
, Tasawar Hayat

Jiangnan University
Qingdao University of Science and Technology
Wuxi Vocational Institute of Commerce
King Abdulaziz University

Research output: Contribution to journal › Article › peer-review

5 Scopus citations

Abstract

This paper focuses on the parameter estimation problem of multivariate output-error autoregressive moving average (M-OEARMA) systems. By applying the auxiliary model identification idea and the decomposition technique, we derive a two-stage recursive least squares algorithm for estimating the M-OEARMA system. Compared with the auxiliary model based recursive least squares algorithm, the proposed algorithm possesses higher identification accuracy. The simulation results confirm the effectiveness of the proposed algorithm.

Original language	English
Pages (from-to)	1547-1557
Number of pages	11
Journal	International Journal of Control, Automation and Systems
Volume	17
Issue number	6
DOIs	https://doi.org/10.1007/s12555-018-0512-0
State	Published - 1 Jun 2019
Externally published	Yes

Keywords

Auxiliary model
decomposition technique
least squares
parameter estimation
recursive identification

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10.1007/s12555-018-0512-0

Cite this

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title = "Two-stage Recursive Least Squares Parameter Estimation Algorithm for Multivariate Output-error Autoregressive Moving Average Systems",

abstract = "This paper focuses on the parameter estimation problem of multivariate output-error autoregressive moving average (M-OEARMA) systems. By applying the auxiliary model identification idea and the decomposition technique, we derive a two-stage recursive least squares algorithm for estimating the M-OEARMA system. Compared with the auxiliary model based recursive least squares algorithm, the proposed algorithm possesses higher identification accuracy. The simulation results confirm the effectiveness of the proposed algorithm.",

keywords = "Auxiliary model, decomposition technique, least squares, parameter estimation, recursive identification",

author = "Yunze Guo and Lijuan Wan and Ling Xu and Feng Ding and Ahmed Alsaedi and Tasawar Hayat",

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year = "2019",

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T1 - Two-stage Recursive Least Squares Parameter Estimation Algorithm for Multivariate Output-error Autoregressive Moving Average Systems

AU - Guo, Yunze

AU - Wan, Lijuan

AU - Xu, Ling

AU - Ding, Feng

AU - Alsaedi, Ahmed

AU - Hayat, Tasawar

PY - 2019/6/1

Y1 - 2019/6/1

N2 - This paper focuses on the parameter estimation problem of multivariate output-error autoregressive moving average (M-OEARMA) systems. By applying the auxiliary model identification idea and the decomposition technique, we derive a two-stage recursive least squares algorithm for estimating the M-OEARMA system. Compared with the auxiliary model based recursive least squares algorithm, the proposed algorithm possesses higher identification accuracy. The simulation results confirm the effectiveness of the proposed algorithm.

AB - This paper focuses on the parameter estimation problem of multivariate output-error autoregressive moving average (M-OEARMA) systems. By applying the auxiliary model identification idea and the decomposition technique, we derive a two-stage recursive least squares algorithm for estimating the M-OEARMA system. Compared with the auxiliary model based recursive least squares algorithm, the proposed algorithm possesses higher identification accuracy. The simulation results confirm the effectiveness of the proposed algorithm.

KW - Auxiliary model

KW - decomposition technique

KW - least squares

KW - parameter estimation

KW - recursive identification

UR - https://www.scopus.com/pages/publications/85065561833

U2 - 10.1007/s12555-018-0512-0

DO - 10.1007/s12555-018-0512-0

M3 - Article

AN - SCOPUS:85065561833

SN - 1598-6446

VL - 17

SP - 1547

EP - 1557

JO - International Journal of Control, Automation and Systems

JF - International Journal of Control, Automation and Systems

IS - 6

ER -

Two-stage Recursive Least Squares Parameter Estimation Algorithm for Multivariate Output-error Autoregressive Moving Average Systems

Abstract

Keywords

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