RECURSIVE SYSTEM IDENTIFICATION

被引：7
作者：
Chen, Han-Fu [1 ]
机构：
[1] Chinese Acad Sci, Inst Syst Sci, AMSS, Key Lab Syst & Control, Beijing 100190, Peoples R China
来源：
ACTA MATHEMATICA SCIENTIA | 2009年 / 29卷 / 03期
关键词：
recursive identification; ARMAX; Hammerstein systems; Wiener systems; nonlinear ARX systems; stochastic approximation; convergence; STOCHASTIC-APPROXIMATION; HAMMERSTEIN SYSTEM; WIENER SYSTEMS; CONVERGENCE; EQUATIONS;
D O I：
10.1016/S0252-9602(09)60062-X
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
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 identification 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 nonlinear ARX systems. The estimates generated by the algorithms are online updated and converge a.s. to the true values as time tends to infinity.
引用
收藏
页码：650 / 672
页数：23
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