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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