Partially-coupled least squares based iterative parameter estimation for multi-variable output-error-like autoregressive moving average systems

This study considers the parameter estimation of a multi-variable output-error-like system with autoregressive moving average noise. In order to solve the problem of the information vector containing unknown variables, a least squares-based iterative algorithm is proposed by using the iterative sear...

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Vydáno v:	IET control theory & applications Ročník 13; číslo 18; s. 3040 - 3051
Hlavní autoři:	Ma, Hao, Pan, Jian, Ding, Feng, Xu, Ling, Ding, Wenfang
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	The Institution of Engineering and Technology 17.12.2019
Témata:	autoregressive moving average noise autoregressive moving average processes gradient methods identification problem information vector iterative methods iterative parameter estimation iterative search least squares approximations multivariable output‐error‐like autoregressive moving average systems multivariable output‐error‐like system parameter estimation parameter vector recursive least squares algorithm redundant parameter estimates Research Article unknown variables vectors iterative methods least squares approximations autoregressive moving average processes multivariable output-error-like autoregressive moving average systems recursive least squares algorithm redundant parameter estimates vectors autoregressive moving average noise parameter vector iterative search information vector identification problem parameter estimation multivariable output-error-like system iterative parameter estimation unknown variables gradient methods
ISSN:	1751-8644, 1751-8652
On-line přístup:	Získat plný text
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