Coupled least squares identification algorithms for multivariate output-error systems
type: Item
instance of: scholarly article
title: Coupled least squares identification algorithms for multivariate output-error systems
zbMATH Open document ID: 1461.93520
author: Wu Huang
author: Feng Ding
published in: Algorithms
publication date: 2018-08-20T00:00:00Z
review text: Summary: This paper focuses on the recursive identification problems for a multivariate output-error system. By decomposing the system into several subsystems and by forming a coupled relationship between the parameter estimation vectors of the subsystems, two coupled auxiliary model based recursive least squares (RLS) algorithms are presented. Moreover, in contrast to the auxiliary model based recursive least squares algorithm, the proposed algorithms provide a reference to improve the identification accuracy of the multivariate output-error system. The simulation results confirm the effectiveness of the proposed algorithms.
Mathematics Subject Classification ID: 93E12
Mathematics Subject Classification ID: 62F10
Mathematics Subject Classification ID: 62M09
Mathematics Subject Classification ID: 93E24
zbMATH DE Number: 6920557
zbMATH Keywords: coupling identification concept
zbMATH Keywords: parameter estimation
zbMATH Keywords: auxiliary model
zbMATH Keywords: least squares
zbMATH Keywords: multivariate system
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.3390/a10010012
OpenAlex ID: W2579168118
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DOI: 10.3390/A10010012
description: scientific article; zbMATH DE number 6920557