A bias-corrected estimator for nonlinear systems with output-error type model structures

Automatica

Volumn 50, Issue 9, 2014, Pages 2373-2380

  Piga, Dario ^a   Tóth, Roland ^b  

^a UNIVERSITY OF APPLIED SCIENCES AND ARTS OF SOUTHERN SWITZERLAND   (Switzerland)

^b EINDHOVEN UNIVERSITY OF TECHNOLOGY   (Netherlands)

Author keywords

Bias corrected least squares estimate; Nonlinear system identification; Output error models

Indexed keywords

ERRORS; MODEL STRUCTURES; NONLINEAR SYSTEMS; OPTIMIZATION;

COMPUTATIONALLY EFFICIENT; LEAST SQUARES ESTIMATE; LINEAR TIME-INVARIANT SYSTEM; NONCONVEX OPTIMIZATION PROBLEM; NUMERICAL OPTIMIZATION ALGORITHMS; OUTPUT ERROR MODELS; PARAMETRIC IDENTIFICATION; POLYNOMIAL NONLINEARITIES;

PARAMETER ESTIMATION;

EID: 84908548100     PISSN: 00051098     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.automatica.2014.07.021     Document Type: Article

References (23)

1. Baran, S. (2000). A consistent estimator in general functional errors-in-variables models. Metrika, 51(2), 117-132.
2. Beghelli, S., Guidorzi, R., & Soverini, U. (1990). The frisch scheme in dynamic system identification. Automatica, 26(1), 171-176.
3. Cerone, V., Piga, D., & Regruto, D. (2012). Bounded error identification of Hammerstein systems through sparse polynomial optimization. Automatica, 48(10), 2693-2698.
4. Cerone, V., Piga, D., & Regruto, D. (2013). Computational load reduction in bounded error identification of Hammerstein systems. IEEE Transactions on Automatic Control, 58(5), 1317-1322.
5. Ding, F., Shi, Y., & Chen, T. (2007). Auxiliary model-based least-squares identification methods for Hammerstein output-error systems. Systems & Control Letters, 56(5), 373-380.
6. Diversi, R., Guidorzi, R., & Soverini, U. (2007). Maximum likelihood identification of noisy input-output models. Automatica, 43(3), 464-472.
7. Fazekas, I., & Kukush, A. G. (1997). Asymptotic properties of an estimator in nonlinear functional errors-in-variables models with dependent error terms. Computers and Mathematics with Applications, 34(10), 23-39.
8. Fernando, K. V., & Nicholson, H. (1985). Identification of linear systems with input and output noise: the Koopmans-Levin method. Control Theory and Applications, IEE Proceedings D, 132, 30-36.
9. Hong, M., Söderström, T., & Zheng, W. X. (2007). Accuracy analysis of bias-eliminating least squares estimates for errors-in-variables systems. Automatica, 43(9), 1590-1596.
10. Jun, B. E., & Bernstein, D. S. (2007). Extended least-correlation estimates for errors-in-variables non-linear models. International Journal of Control, 80(2), 256-267.
11. Laurain, V., Gilson, M., & Garnier, H. (2012). Refined instrumental variable methods for Hammerstein Box-Jenkins models. In System identification, environmental modelling, and control system design (pp. 27-47).
12. Laurain, V., Gilson, M., Tóth, R., & Garnier, H. (2010). Refined instrumental variable methods for identification of LPV Box-Jenkins models. Automatica, 46(6), 959-967.
13. Ljung, L. (1999). System identification, theory for the user. Upper Saddle River: Prentince Hall.
14. Ljung, L. (2010). Perspectives on system identification. Annual Reviews in Control, 34(1), 1-12.
15. Ninness, B. (2000). Strong laws of large numbers under weak assumptions with application. IEEE Transactions on Automatic Control, 45(11), 2117-2122.
16. Söderström, T., & Stoica, P. (1983). Instrumental variable methods for system identification: Vol. 161. Berlin: Springer-Verlag.
17. Stoica, P., & Söderström, T. (1982). Bias correction in least-squares identification. International Journal of Control, 35(3), 449-457.
18. Vajk, I., & Hetthéssy, J. (2003). Identification of nonlinear errors-in-variables models. Automatica, 39(12), 2099-2107.
19. Vandersteen, G., Rolain, Y., Schoukens, J., & Pintelon, R. (1996). On the use of system identification for accurate parametric modeling of nonlinear systems using noisy measurements. IEEE Transactions on Instrumentation and Measurement, 45(2), 605-609.
20. Wang, J., Zhang, Q., & Ljung, L. (2009). Revisiting Hammerstein system identification through the two-stage algorithm for bilinear parameter estimation. Automatica, 45(11), 2627-2633.
21. Zheng, W. X. (1998). Transfer function estimation from noisy input and output data. International Journal of Adaptive Control and Signal Processing, 12(4), 365-380.
22. Zheng, W. X. (2002). A bias correction method for identification of linear dynamic errors-in-variables models. IEEE Transactions on Automatic Control, 47(7), 1142-1147.
23. Zhu, Y. (2002). Estimation of an N-L-N Hammerstein-Wiener model. Automatica, 38(9), 1607-1614.