数学物理学报(英文版) ›› 2009, Vol. 29 ›› Issue (3): 650-672.doi: 10.1016/S0252-9602(09)60062-X

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RECURSIVE SYSTEM IDENTIFICATION

陈翰馥   

  1. Key Laboratory of Systems and Control, Institute of Systems Science, AMSS Chinese Academy of Sciences, Beijing 100190, China
  • 收稿日期:2008-12-10 出版日期:2009-05-20 发布日期:2009-05-20
  • 基金资助:

    The work is supported by NSFC (60221301 and 60874001) and by a grant from the National Laboratory of Space Intelligent Control

RECURSIVE SYSTEM IDENTIFICATION

Han-Fu Chen   

  1. Key Laboratory of Systems and Control, Institute of Systems Science, AMSS Chinese Academy of Sciences, Beijing 100190, China
  • Received:2008-12-10 Online:2009-05-20 Published:2009-05-20
  • Supported by:

    The work is supported by NSFC (60221301 and 60874001) and by a grant from the National Laboratory of Space Intelligent Control

摘要:

Most of existing methods in system identification with possible exception of those for linear systems are off-line in nature, and hence are nonrecursive. This paper demonstrates the recent progress in recursive system identification. The recursive identifi-cation algorithms are presented not only for linear systems (multivariate ARMAX systems) but also for nonlinear systems such as the Hammerstein and Wiener systems, and the non-
linear ARX systems. The estimates generated by the algorithms are online updated and converge a.s. to the true values as time tends to infinity.

关键词: recursive identification, ARMAX, Hammerstein systems, Wiener systems, nonlinear ARX systems, stochastic approximation, convergence

Abstract:

Most of existing methods in system identification with possible exception of those for linear systems are off-line in nature, and hence are nonrecursive. This paper demonstrates the recent progress in recursive system identification. The recursive identifi-cation algorithms are presented not only for linear systems (multivariate ARMAX systems) but also for nonlinear systems such as the Hammerstein and Wiener systems, and the non-
linear ARX systems. The estimates generated by the algorithms are online updated and converge a.s. to the true values as time tends to infinity.

Key words: recursive identification, ARMAX, Hammerstein systems, Wiener systems, nonlinear ARX systems, stochastic approximation, convergence

中图分类号: 

  • 93E12