“System Identification in a MIC perspective”

Authors: Lennart Ljung,
Affiliation: Linköping University
Reference: 1994, Vol 15, No 3, pp. 153-159.

Keywords: Identification, modeling, model errors, disturbance models

Abstract: The paper describes some subjective aspects on some current research topics in system identification. A ´classical´ standpoint is taken regarding complexity models. The need for specific tools for ´semi-physical-modeling´ is also pointed out, and a discussion on different disturbance models is also included.

PDF PDF (1054 Kb)        DOI: 10.4173/mic.1994.3.4

DOI forward links to this article:
[1] R. Vilanova and P. Balaguer (2009), doi:10.1049/iet-cta:20070483
[2] J.M. Boling and P.M. Makila (1998), doi:10.1109/9.668839
[3] P.M. Mäkilä, J.R. Partington and T.K. Gustafsson (1995), doi:10.1016/0005-1098(95)00106-3
[4] Biao Huang and Sirish L. Shah (1997), doi:10.1016/S0959-1524(97)00019-X
[5] John Doty and Jose Camberos (2010), doi:10.2514/6.2010-278
[6] J.M. Boling and P.M. Makila (1995), doi:10.1109/ACC.1995.532082
[7] Pedro Balaguer and Ramon Vilanova (2006), doi:10.1109/CDC.2006.377513
[8] Pedro Balaguer, Ramon Vilanova and Asier Ibeas (2006), doi:10.1109/CESA.2006.4281685
References:
[1] DRAPER, N.R. SMITH, H. (1981). Applied Regression Analysis, 2nd ed, Wiley, New York.
[2] ELMQUIST, H. (1993). Object-oriented modeling anti automatic formula manipulation in Dymola, In Proc. SIMS´93, Scandinavian Simulation Society, Kongsberg, Norway, June, 1993, pp. 97-105.
[3] FOGEL, E. (1979). System identification via membership set constraints with energy constrained noise, IEEE Trans. on Automatic Control, 24, 615-622 doi:10.1109/TAC.1979.1102164
[4] GEVERS, M. (1993). Towards a joint design of identification and control?, In H. L. Trentelman and J. C. Willems, eds, Essays on control: Perspectives in the theory and its applications, ECC ´93 Groningen.
[5] GUO, L LJUNG, L. (1994). The role of model validation for assessing the size of the unmodelled dynamics, Technical Report LiTH-ISY-I, Department of Electrical Engineering.
[6] HJALMARSSON, H. LJUNG, L. (1993). A discussion of ´unknown-but-bounded´ disturbances in system identification, In Proc. 32nd IEEE Conf. on Decision and Control, San Antonio, Texas, 1993.
[7] KALMAN, R.E. (1958). Design of a self-optimizing control system, Transaction ASME, Journal of Basic Engineering, 80, 468-478.
[8] KOSUT, R.L., GOODWIN, G.C. POLIS, M.P. (1992). Special Issue on System Identification for Robust Control Design, IEEE Trans. Automatic Control, 37.
[9] LINDSKOG, P. LJUNG, L. (1994). Tools for semi-physical modelling, In Proc. IFAC Symposium on Identification and System Parameter Estimation, Copenhagen, Denmark.
[10] LJUNG, L,. (1987). System Identification-Theory for the User, Prentice-Hall, Englewood Cliffs, N.J.
[11] MÄKILÄ, P. PARTINGTON, J. (1991). Robust approximation and identification in H-Infinity, Proc. American Control Conference, pp. 70-76.
[12] MILANESE, M. TEMPO, R. (1985). Optimal algorithms for robust estimation and prediction, IEEE Trans. Automatic Control, 30,730-738 doi:10.1109/TAC.1985.1104056
[13] NAGY, P.A.J. LJUNG, L. (1991). System identification using bond graphs, In Proceedings of the European Control Conferences, 3, pp. 2564-2569, Grenoble.
[14] SCHWEPPE, F.C. (1968). Recursive state estimation--unknown but bounded errors and system inputs, IEEE Trans. on Automatic. Control, 37, 22-28.


BibTeX:
@article{MIC-1994-3-4,
  title={{System Identification in a MIC perspective}},
  author={Ljung, Lennart},
  journal={Modeling, Identification and Control},
  volume={15},
  number={3},
  pages={153--159},
  year={1994},
  doi={10.4173/mic.1994.3.4},
  publisher={Norwegian Society of Automatic Control}
};