“Dynamic system calibration: the low primary output sampling rate case”

Authors: Rolf Ergon,
Affiliation: Telemark University College
Reference: 1998, Vol 19, No 2, pp. 99-107.

Keywords: Product quality, estimation, system identification

Abstract: In many industrial cases it is not feasible to measure primary outputs, e.g. product quality, from production processes on-line. It is thus of interest to estimate such outputs from known process inputs and secondary process measurements. In an earlier paper it is shown that optimal estimators can be identified from data recorded during an informative experiment, with the primary outputs sampled at the same high rate as the inputs and secondary outputs. In the present paper it is shown that optimal estimators can also be found from data where the primary outputs are sampled at a low and possibly irregular rate.

PDF PDF (1117 Kb)        DOI: 10.4173/mic.1998.2.3

DOI forward links to this article:
[1] Rolf Ergon and Maths Halstensen (2001), doi:10.4173/mic.2001.2.2
[2] Rolf Ergon and Maths Halstensen (2000), doi:10.1002/1099-128X(200009/12)14:5/6<617::AID-CEM618>3.0.CO;2-M
[3] Rolf Ergon (2007), doi:10.4173/mic.2007.1.2
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[2] ERGON, R. DI RUSCIO, D. (1997). Dynamic system calibration by system identification methods, The European Control Conference, ECC97, Brussels, CD file ECC416.pdf.
[3] ERGON, R. (1998). Dynamic system multivariate calibration, Modeling, Identification and Control, Vol. 19, No. 2 doi:10.4173/mic.1998.2.2
[4] ERGON, R. (1999). On Primary Output Estimation by use of Secondary Measurements as Input Signals in System Identification, scheduled for publication in IEEE Transactions on Automatic Control, April 1999.
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BibTeX:
@article{MIC-1998-2-3,
  title={{Dynamic system calibration: the low primary output sampling rate case}},
  author={Ergon, Rolf},
  journal={Modeling, Identification and Control},
  volume={19},
  number={2},
  pages={99--107},
  year={1998},
  doi={10.4173/mic.1998.2.3},
  publisher={Norwegian Society of Automatic Control}
};