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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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