Identification of unknown parameters in linear discrete-time systems by a modified extended Kalman filter
作者:
T. YOSHIMURA,
K. KONISHI,
R. KIYOZUMI,
T. SOEDA,
期刊:
International Journal of Systems Science
(Taylor Available online 1980)
卷期:
Volume 11,
issue 1
页码: 97-105
ISSN:0020-7721
年代: 1980
DOI:10.1080/00207728008966999
出版商: Taylor & Francis Group
数据来源: Taylor
摘要:
This paper treats an identification technique for discrete-time linear systems whim noisy measurements are taken. The technique is based on the extended Kalman filter and the model reference adaptive approach. Firstly, the extended Kalman filter derived by augmenting unknown parameters as the state variables is modified by neglecting the information between the states and unknown parameters ; and secondly the stability of the modified filter is compensated by the idea of the model reference adaptive approach. Lastly, the convergence of the obtained estimates for unknovm parameters to the exact values is proved. A numerical example shows the effectiveness of the proposed method.
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