Comparison of Prediction Models for a Dual-Hormone Artificial Pancreas

Dimitri Boiroux, Vladimír Bátora, Morten Hagdrup, Marían Tárnik, Ján Murgaš, Signe Schmidt, Kirsten Nørgaard, Niels Kjølstad Poulsen, Henrik Madsen, John Bagterp Jørgensen

Research output: Contribution to journalConference articleResearchpeer-review

535 Downloads (Pure)

Abstract

In this paper we compare the performance of five different continuous time transfer function models used in closed-loop model predictive control (MPC). These models describe the glucose-insulin and glucose-glucagon dynamics. They are discretized into a state-space description and used as prediction models in the MPC algorithm. We simulate a scenario including meals and daily variations in the model parameters. The numerical results do not show significant changes in the glucose traces for any of the models, excepted for the first order model. From the present study, we can conclude that the second order model without delay should provide the best trade-off between sensitivity to uncertainties and practical usability for in vivo clinical studies.
Original languageEnglish
Book seriesI F A C Workshop Series
Volume48
Issue number20
Pages (from-to)7-12
ISSN1474-6670
DOIs
Publication statusPublished - 2015
Event9th IFAC Symposium on Biological and Medical Systems (BMS 2015) - Berlin, Germany
Duration: 31 Aug 20152 Sep 2015
Conference number: 9
http://www.bms2015.org/

Conference

Conference9th IFAC Symposium on Biological and Medical Systems (BMS 2015)
Number9
CountryGermany
CityBerlin
Period31/08/201502/09/2015
Internet address

Keywords

  • Type 1 Diabetes
  • Artificial Pancreas
  • Model Predictive Control

Fingerprint Dive into the research topics of 'Comparison of Prediction Models for a Dual-Hormone Artificial Pancreas'. Together they form a unique fingerprint.

Cite this