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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