Design of luenberger observer for glucose-insulin control via Mathematica

L. Kovács, Béla Paláncz, Z. Benyó

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

Many articles dealing with insulin-glucose control have been published in the last decades, and they mostly assumed that all the system state variables are available for feedback. However, this is not usually the case, or they are not so cheap in practice as blood glucose measurements are. In this paper the use of the reduced-order estimator (also known as the Luenberger observer) is considered in symbolic form employing Polynomial Control System Application of Mathematica for the three-state minimal Bergman model, [1], as this can be used to reconstruct those state variables that are hard to be recovered directly from the system outputs: remote compartment insulin and plasma insulin. Nonlinear closed loop simulations with H2/H control (disturbance rejection LQ method) showed that the observer, which is faster than the system itself, can provide a very good state recovery performance.

Original languageEnglish
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Pages624-627
Number of pages4
DOIs
Publication statusPublished - 2007
Event29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07 - Lyon, France
Duration: Aug 23 2007Aug 26 2007

Other

Other29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07
CountryFrance
CityLyon
Period8/23/078/26/07

Fingerprint

Insulin
Glucose
Control system applications
Disturbance rejection
Blood
Polynomials
Feedback
Plasmas
Recovery

ASJC Scopus subject areas

  • Biomedical Engineering

Cite this

Kovács, L., Paláncz, B., & Benyó, Z. (2007). Design of luenberger observer for glucose-insulin control via Mathematica. In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings (pp. 624-627). [4352367] https://doi.org/10.1109/IEMBS.2007.4352367

Design of luenberger observer for glucose-insulin control via Mathematica. / Kovács, L.; Paláncz, Béla; Benyó, Z.

Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. 2007. p. 624-627 4352367.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kovács, L, Paláncz, B & Benyó, Z 2007, Design of luenberger observer for glucose-insulin control via Mathematica. in Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings., 4352367, pp. 624-627, 29th Annual International Conference of IEEE-EMBS, Engineering in Medicine and Biology Society, EMBC'07, Lyon, France, 8/23/07. https://doi.org/10.1109/IEMBS.2007.4352367
Kovács L, Paláncz B, Benyó Z. Design of luenberger observer for glucose-insulin control via Mathematica. In Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. 2007. p. 624-627. 4352367 https://doi.org/10.1109/IEMBS.2007.4352367
Kovács, L. ; Paláncz, Béla ; Benyó, Z. / Design of luenberger observer for glucose-insulin control via Mathematica. Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. 2007. pp. 624-627
@inproceedings{d188ed478b5b44969f41129c25b726a2,
title = "Design of luenberger observer for glucose-insulin control via Mathematica",
abstract = "Many articles dealing with insulin-glucose control have been published in the last decades, and they mostly assumed that all the system state variables are available for feedback. However, this is not usually the case, or they are not so cheap in practice as blood glucose measurements are. In this paper the use of the reduced-order estimator (also known as the Luenberger observer) is considered in symbolic form employing Polynomial Control System Application of Mathematica for the three-state minimal Bergman model, [1], as this can be used to reconstruct those state variables that are hard to be recovered directly from the system outputs: remote compartment insulin and plasma insulin. Nonlinear closed loop simulations with H2/H∞ control (disturbance rejection LQ method) showed that the observer, which is faster than the system itself, can provide a very good state recovery performance.",
author = "L. Kov{\'a}cs and B{\'e}la Pal{\'a}ncz and Z. Beny{\'o}",
year = "2007",
doi = "10.1109/IEMBS.2007.4352367",
language = "English",
isbn = "1424407885",
pages = "624--627",
booktitle = "Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings",

}

TY - GEN

T1 - Design of luenberger observer for glucose-insulin control via Mathematica

AU - Kovács, L.

AU - Paláncz, Béla

AU - Benyó, Z.

PY - 2007

Y1 - 2007

N2 - Many articles dealing with insulin-glucose control have been published in the last decades, and they mostly assumed that all the system state variables are available for feedback. However, this is not usually the case, or they are not so cheap in practice as blood glucose measurements are. In this paper the use of the reduced-order estimator (also known as the Luenberger observer) is considered in symbolic form employing Polynomial Control System Application of Mathematica for the three-state minimal Bergman model, [1], as this can be used to reconstruct those state variables that are hard to be recovered directly from the system outputs: remote compartment insulin and plasma insulin. Nonlinear closed loop simulations with H2/H∞ control (disturbance rejection LQ method) showed that the observer, which is faster than the system itself, can provide a very good state recovery performance.

AB - Many articles dealing with insulin-glucose control have been published in the last decades, and they mostly assumed that all the system state variables are available for feedback. However, this is not usually the case, or they are not so cheap in practice as blood glucose measurements are. In this paper the use of the reduced-order estimator (also known as the Luenberger observer) is considered in symbolic form employing Polynomial Control System Application of Mathematica for the three-state minimal Bergman model, [1], as this can be used to reconstruct those state variables that are hard to be recovered directly from the system outputs: remote compartment insulin and plasma insulin. Nonlinear closed loop simulations with H2/H∞ control (disturbance rejection LQ method) showed that the observer, which is faster than the system itself, can provide a very good state recovery performance.

UR - http://www.scopus.com/inward/record.url?scp=57649244003&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=57649244003&partnerID=8YFLogxK

U2 - 10.1109/IEMBS.2007.4352367

DO - 10.1109/IEMBS.2007.4352367

M3 - Conference contribution

SN - 1424407885

SN - 9781424407880

SP - 624

EP - 627

BT - Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings

ER -