Identification of errors-in-variables systems with ARMA measurement noises

被引：0

作者：

Song Qijiang ^{[1
]}

Chen Hanfu ^{[2
]}

机构：

[1] Chinese Acad Sci, AMSS, Beijing 100080, Peoples R China

[2] Chinese Acad Sci, AMSS, Inst Syst Sci, Beijing 100080, Peoples R China

来源：

PROCEEDINGS OF THE 26TH CHINESE CONTROL CONFERENCE, VOL 3 | 2007年

关键词：

errors-in-variables (EIV); identification; Stochastic approximation (SA); ARMA; recursive estimate; strong consistency;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The paper concerns identification problem of the single-input single-output errors-in-variables (EIV) systems with ARMA measurement noises using iid input. Recursive estimates are given for parameters of EIV systems. The strong consistency of the recursive algorithms is proved. A simulation example is provided, which justifies the theoretical results.

引用

页码：292 / +

页数：2

共 13 条

[1] AGUERO JC, 2006, IFAC S SYSTEM IDENTI
[2] IDENTIFICATION OF SCALAR ERRORS-IN-VARIABLES MODELS WITH DYNAMICS
ANDERSON, BDO
[J]. AUTOMATICA, 1985, 21 (06) : 709 - 716
[3] [Anonymous], 1978, PROBABILITY THEORY
[4] Chen H.-F., 2002, Stochastic Approximation and Its Applications
[5] Strongly consistent coefficient estimate for errors-in-variables models
Chen, HF
Yang, JM
[J]. AUTOMATICA, 2005, 41 (06) : 1025 - 1033
[6] CHEN HF, 2006, CHIN CONTR C
[7] EKMAN M, 2006, 14 IFAC S SYST IDENT
[8] Identification for Wiener systems with RTF subsystems
Hu, Xiao-Li
Chen, Han-Fu
[J]. EUROPEAN JOURNAL OF CONTROL, 2006, 12 (06) : 581 - 594
[9] Convergence properties of bias-eliminating algorithms for errors-in-variables identification
Söderström, T
Hong, M
Zheng, WX
[J]. INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING, 2005, 19 (09) : 703 - 722
[10] Identification of dynamic errors-in-variables models:: Approaches based on two-dimensional ARMA modeling of the data
Söderström, T
Mahata, K
Soverini, U
[J]. AUTOMATICA, 2003, 39 (05) : 929 - 935

← 1 2 →