Parameter identification in lumped linear continuous systems in a noisy environment via Kalman-filtered Poisson moment functionals
作者:
LINGAPPAN SIVAKUMAR,
GANTI PRASADA RAO,
期刊:
International Journal of Control
(Taylor Available online 1982)
卷期:
Volume 35,
issue 3
页码: 509-519
ISSN:0020-7179
年代: 1982
DOI:10.1080/00207178208922635
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
This paper presents a Poisson moment functional (PMF) approach to parameter identification in lumped linear continuous systems in a noisy environment. The method is based on initially Kalman-filtering the PMFs and then employing them in the established general algorithms. This Kalman-filtered Poisson moment Functional (KFPMF) method is shown to be superior to the conventional least squares approach through an illustrative example.
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