Hierarchical Recursive Gradient Parameter Identification for Multi‐Input ARX Systems With Partially‐Coupled Information Vectors

ABSTRACT The research object of coupling identification is for multivariate systems. It is required to study and explore recursive and iterative identification methods for multivariable systems when there exists information coupling and/or parameter coupling between their subsystems. For a multivariable system, namely a multiple‐input multiple‐output system, after parameterization, its identification model contains the same information vector in all its subsystems. For a multi‐input ARX system where there exists the information vector coupling, this paper derives the coupled identification model and investigates recursive parameter identification methods for such partially‐coupled information vector systems, and presents a hierarchical recursive gradient identification algorithm and a hierarchical multi‐innovation recursive gradient identification algorithm. Finally, the simulation example is provided to show the effectiveness of the proposed algorithms.

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Publication Details

Journal
International Journal of Adaptive Control and Signal Processing
Published
2025-06-18
DOI
https://doi.org/10.1002/acs.4036
Citations
43
Primary Topic
Control Systems and Identification
Type
article
Field-Weighted Citation Impact
52.22

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article

Hierarchical Recursive Gradient Parameter Identification for Multi‐Input ARX Systems With Partially‐Coupled Information Vectors

Ling Xu, Xiaoli Luan, Feng Ding, Zhang Xiao
43 citations
International Journal of Adaptive Control and Signal Processing
Control Systems and Identification
52.22
article

Hierarchical Recursive Gradient Parameter Identification for Multi‐Input ARX Systems With Partially‐Coupled Information Vectors

Ling Xu, Xiaoli Luan, Feng Ding, Zhang Xiao
article en
43 citations

Abstract

ABSTRACT The research object of coupling identification is for multivariate systems. It is required to study and explore recursive and iterative identification methods for multivariable systems when there exists information coupling and/or parameter coupling between their subsystems. For a multivariable system, namely a multiple‐input multiple‐output system, after parameterization, its identification model contains the same information vector in all its subsystems. For a multi‐input ARX system where there exists the information vector coupling, this paper derives the coupled identification model and investigates recursive parameter identification methods for such partially‐coupled information vector systems, and presents a hierarchical recursive gradient identification algorithm and a hierarchical multi‐innovation recursive gradient identification algorithm. Finally, the simulation example is provided to show the effectiveness of the proposed algorithms.

International Journal of Adaptive Control and Signal ProcessingVol. 39(9)
Jiangnan University (CN), Wuhan Donghu University (CN), Changzhou University (CN), Hubei University of Technology (CN)
National Natural Science Foundation of China, Natural Science Foundation of Jiangsu Province
Industry, innovation and infrastructure
Openalex Percentile: Top 0%
Control Systems and Identification
52.22
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