Identification of a two-input system: Variance analysis

IFAC Proceedings Volumes (IFAC-PapersOnline)

Volumn 38, Issue 1, 2005, Pages 674-679

  Gevers, M ^a   Miskovic L ^b   Bonvin, D ^b   Karimi, A ^b  

^a Catholic University of Louvain   (Belgium)

^b EPFL   (Switzerland)

Author keywords

Identification; Input design; Two input systems; Variance analysis

Indexed keywords

ARMAX MODEL; EXPERIMENT DESIGN; INPUT DESIGN; INPUT SYSTEMS; POLYNOMIAL COEFFICIENTS; SIGNAL-ON; VARIANCE ANALYSIS;

IDENTIFICATION (CONTROL SYSTEMS);

EID: 79960715362     PISSN: 14746670     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.3182/20050703-6-cz-1902.00113     Document Type: Conference Paper

References (8)

1. Dayal, B. S. and J. F. MacGregor (1997). Multi-output process identification. Journal of Process Control 7(4), 269-282.
2. Garatti, S., M. C. Campi and S. Bittanti (2004). Assessing the quality of identified models through the asymptotic theory - when is the result reliable?. Automatica 40, 1319-1332.
3. Klein, A. A. B. and G. Mélard (1994). The information matrix of multiple-input single-output time series models. Journal of Computational and Applied Mathematics 51, 349-356.
4. Ljung, L. (1999). System Identification: Theory for the User, 2nd Edition. Prentice-Hall. Englewood Cliffs, NJ.
5. Ninness, B. and H. Hjalmarsson (2004). Variance error quantifications that are exact for finitemodel order. IEEE Trans. Automatic Control 49(8), 1275-1291.
6. Xie, L. L. and L. Ljung (2001). Asymptotic variance expressions for estimated frequency functions. IEEE Trans. Automatic Control 46(12), 1887- 1889.
7. Zhu, Y. C. (1998). Multivariable process identification for MPC: the asymptotic method and its applications. Journal of Process Control 8(2), 101-115.
8. Zhu, Y. C. and T. Backx (1993). Identification of multivariable industrial processes for simulation, diagnosis and control. In: Advances in Industrial Control (M. J. Grimble and M. A. Johnson, Eds.). Springer-Verlag. London.