Recursive Algorithms for Multivariable Output-Error-Like ARMA Systems

This paper studies the parameter identification problems for multivariable output-error-like systems with colored noises. Based on the hierarchical identification principle, the original system is decomposed into several subsystems. However, each subsystem contains the same parameter vector, which l...

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Bibliographic Details
Main Authors: Hao Ma, Jian Pan, Lei Lv, Guanghui Xu, Feng Ding, Ahmed Alsaedi, Tasawar Hayat
Format: Article
Language:English
Published: MDPI AG 2019-06-01
Series:Mathematics
Subjects:
Online Access:https://www.mdpi.com/2227-7390/7/6/558
Description
Summary:This paper studies the parameter identification problems for multivariable output-error-like systems with colored noises. Based on the hierarchical identification principle, the original system is decomposed into several subsystems. However, each subsystem contains the same parameter vector, which leads to redundant computation. By taking the average of the parameter estimation vectors of each subsystem, a partially-coupled subsystem recursive generalized extended least squares (PC-S-RGELS) algorithm is presented to cut down the redundant parameter estimates. Furthermore, a partially-coupled recursive generalized extended least squares (PC-RGELS) algorithm is presented to further reduce the computational cost and the redundant estimates by using the coupling identification concept. Finally, an example indicates the effectiveness of the derived algorithms.
ISSN:2227-7390