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Recursive identification of linear and non-linear systems

 

作者: A. K. SINHA,   A. K. MAHALANABIS,  

 

期刊: International Journal of Systems Science  (Taylor Available online 1974)
卷期: Volume 5, issue 11  

页码: 1065-1076

 

ISSN:0020-7721

 

年代: 1974

 

DOI:10.1080/00207727408920162

 

出版商: Taylor & Francis Group

 

数据来源: Taylor

 

摘要:

The paper develops recursive techniques for off-line identification of linear and nonlinear systems. It is shown that if the system is linear and time invariant, impulse response characterization of the system coupled with an orthogonal series approximation can be utilized for the purpose stated above. The techniques of adaptive Kalman filtering are shown to be applicable, which besides permitting recursive evaluation of the coefficients, lead to a number of important advantages. In the second part of the study, the proposed method is extended for recursive identification of a class of non-linear systems which can be represented as a cascade combination of a linear dynamical system and a non-linear zero memory system. The method of Volterra series representation of such systems is utilized. Results are illustrated through numerical examples in each case.

 

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