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On‐line parameter interval estimation using recursive least squares

 

作者: Per‐Olof Gutman,  

 

期刊: International Journal of Adaptive Control and Signal Processing  (WILEY Available online 1994)
卷期: Volume 8, issue 1  

页码: 61-72

 

ISSN:0890-6327

 

年代: 1994

 

DOI:10.1002/acs.4480080106

 

出版商: Wiley Subscription Services, Inc., A Wiley Company

 

关键词: Least‐squares estimation;Parameter estimation;Recursive least squares;Set membership estimation

 

数据来源: WILEY

 

摘要:

AbstractA bank of recursive least‐squares (RLS) estimators is proposed for the estimation of the uncertainty intervals of the parameters of an equation error model (or RLS model) where the equation error is assumed to lie between known upper and lower bounds. It is shown that the off‐line least‐squares method gives the maximum and minimum parameter values that could have produced the recorded input‐output sequence. By modifying the RLS estimator in two ways, it is possible to recursively compute inner and outer bounds of the uncertainty intergals. It is shown that the inner bound is asymptoticall

 

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