A generalized instrumental variable estimation method for errors-in-variables identification problems

Automatica

Volumn 47, Issue 8, 2011, Pages 1656-1666

  Söderström, Torsten ^a  

^a UPPSALA UNIVERSITY   (Sweden)

Author keywords

Covariance functions; Covariance matrix; Errors in variables models; Linear systems; System identification

Indexed keywords

ASYMPTOTIC DISTRIBUTIONS; COMPUTATIONAL ASPECTS; COVARIANCE FUNCTION; ERRORS IN VARIABLES; ERRORS-IN-VARIABLES MODELS; ESTIMATION METHODS; IDENTIFICATION PROBLEM; INPUT AND OUTPUTS; INSTRUMENTAL VARIABLES; PARAMETER ESTIMATE; SYSTEM IDENTIFICATIONS;

COVARIANCE MATRIX; ESTIMATION; LINEAR SYSTEMS; PARAMETER ESTIMATION;

ERRORS;

EID: 79960896426     PISSN: 00051098     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.automatica.2011.05.010     Document Type: Article

References (23)

1. Beghelli, S.; Castaldi, P.; Guidorzi, R.; & Soverini, U. (1993). A robust criterion for model selection in identification from noisy data. In Proc. 9th international conference on systems engineering. Las Vegas, Nevada, USA (pp. 480484).
2. S. Beghelli, R.P. Guidorzi, and U. Soverini The Frisch scheme in dynamic system identification Automatica 26 1990 171 176
3. Diversi, R.; Guidorzi, R.; & Soverini, U. (2003). A new criterion in EIV identification and filtering applications. In Proc. 13th IFAC symposium on system identification. Rotterdam, The Netherlands. August 2729 (pp. 19931998).
4. Diversi, R.; Guidorzi, R.; & Soverini, U. (2004). Frisch scheme-based algorithms for EIV identification. In Proc. 12th IEEE mediterranean conference on control and automation. Kusadasi, Turkey, June.
5. Diversi, R.; Soverini, U.; & Guidorzi, R. (2006). Yule-Walker equations in the Frisch scheme solution of errors-in-variables identification problems. In Proc. 17th international symposium on mathematical theory of networks and systems. MTNS. Kyoto, Japan. July (pp. 391395).
6. Ekman, M. (2005). Identification of linear systems with errors in variables using separable nonlinear least squares. In 16th IFAC world congress. Prague, Czech Republic. July 0408.
7. Ekman, M.; Hong, M.; & Söderström, T. (2006). A separable nonlinear least squares approach for identification of linear systems with errors in variables. In Proc. 14th IFAC symposium on system identification. Newcastle, Australia. March 2931.
8. M. Hong, and T. Söderström Relations between bias-eliminating least squares, the Frisch scheme and extended compensated least squares methods for identifying errors-in-variables systems Automatica 45 1 2009 277 282
9. Hong, M.; Söderström, T.; Soverini, U.; & Diversi, R. (2008). Comparison of three Frisch methods for errors-in-variables identification. In IFAC 17th world congress. Seoul, Korea. July 0611.
10. M. Hong, T. Söderström, and W.X. Zheng Accuray analysis of bias-eliminating least squares estimates for errors-in-variables systems Automatica 43 9 2007 1590 1596 (Pubitemid 47198202)
11. L. Ljung, and T. Söderström Theory and practice of recursive identification 1983 MIT Press Cambridge, MA, USA
12. T. Söderström Accuracy analysis of the Frisch estimates for identifying errors-in-variables systems IEEE Transactions on Automatic Control 52 6 2007 985 997 (Pubitemid 47034026)
13. T. Söderström Errors-in-variables methods in system identification Automatica 43 6 2007 939 958 Survey paper (Pubitemid 46653815)
14. T. Söderström Extending the Frisch scheme for errors-in-variables identification to correlated noise International Journal of Adaptive Control and Signal Processing 22 1 2008 55 73 (Pubitemid 351315657)
15. Söderström, T. (2009). Expressions for the covariance matrix of covariance data. Technical report 2009-016. Department of Information Technology. Uppsala University. Uppsala, Sweden. Available as: http://www.it.uu.se/research/publications/reports/2009-016.
16. T. Söderström, and M. Mossberg Accuracy analysis of a covariance matching approach for identifying errors-in-variables systems Automatica 47 1 2011 272 282
17. T. Söderström, M. Mossberg, and M. Hong A covariance matching approach for identifying errors-in-variables systems Automatica 45 9 2009 2018 2031
18. T. Söderström, and P. Stoica Instrumental variable methods for system identification 1983 Springer-Verlag Berlin
19. T. Söderström, and P. Stoica System identification 1989 Prentice Hall International Hemel Hempstead, UK
20. S. Van Huffel Recent advances in total least squares techniques and errors-in-variables modelling 1997 SIAM Philadelphia, USA
21. S. Van Huffel, and Ph. Lemmerling Total least squares and errors-in-variables modelling. analysis, algorithms and applications 2002 Kluwer Dordrecht, The Netherlands
22. W.X. Zheng Transfer function estimation form noisy input and output data International Journal of Adaptive Control and Signal Processing 12 1998 365 380 (Pubitemid 128552839)
23. W.X. Zheng A bias correction method for identification of linear dynamic errors-in-variables models IEEE Transactions on Automatic Control 47 7 2002 1142 1147 (Pubitemid 34835341)