Recursive coupled projection algorithms for multivariable output-error-like systems with coloured noises

By combining the coupling identification concept with the gradient search, this study develops a partially coupled generalised extended projection algorithm and a partially coupled generalised extended stochastic gradient algorithm to estimate the parameters of a multivariable output-error-like syst...

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Bibliographic Details
Published in:IET signal processing Vol. 14; no. 7; pp. 455 - 466
Main Authors: Pan, Jian, Ma, Hao, Zhang, Xiao, Liu, Qinyao, Ding, Feng, Chang, Yufang, Sheng, Jie
Format: Journal Article
Language:English
Published: The Institution of Engineering and Technology 01.09.2020
Subjects:
autoregressive moving average noise
autoregressive moving average processes
coloured noises
coupled relationship
coupling identification concept
gradient methods
gradient search
hierarchical identification principle
identification
identification model
input–output data
least squares approximations
multivariable control systems
multivariable output‐error‐like system
parameter estimation
parameter estimation algorithm
projection algorithm
recursive coupled projection algorithms
Research Article
state‐space methods
stochastic gradient algorithm
stochastic processes
least squares approximations
coupled relationship
coupling identification concept
autoregressive moving average processes
coloured noises
stochastic gradient algorithm
parameter estimation algorithm
projection algorithm
input–output data
identification
autoregressive moving average noise
multivariable control systems
gradient search
identification model
hierarchical identification principle
parameter estimation
multivariable output-error-like system
stochastic processes
gradient methods
recursive coupled projection algorithms
state-space methods
ISSN:1751-9675, 1751-9683, 1751-9683
Online Access:Get full text
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Summary:By combining the coupling identification concept with the gradient search, this study develops a partially coupled generalised extended projection algorithm and a partially coupled generalised extended stochastic gradient algorithm to estimate the parameters of a multivariable output-error-like system with autoregressive moving average noise from input–output data. The key is to divide the identification model into several submodels based on the hierarchical identification principle and to establish the parameter estimation algorithm by using the coupled relationship between these submodels. The simulation test results indicate that the proposed algorithms are effective.
ISSN:1751-9675
1751-9683
1751-9683
DOI:10.1049/iet-spr.2019.0481