Model predictive control for type 1 diabetes based on personalized linear time-varying subject model consisting of both insulin and meal inputs: In Silico evaluation

Qian Wang, Jinyu Xie, Peter Molenaar, Jan Ulbrecht

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

3 Citations (Scopus)

Abstract

An essential component of insulin therapy for type 1 diabetes involves the prediction of blood glucose levels as function of exogenous perturbations such as insulin dose and meal intake. Based on the authors' previously developed patient-specific linear time-varying model for glucose dynamics consisting of both insulin and meal inputs, this paper develops a model predictive control for determining the optimal insulin delivery to regulate blood glucose in euglycemic range. Evaluation of the developed controller using the UVa/Padova simulator shows promising results. In addition, results in this paper show the importance of explicitly including the meal intake in the regression model, which was often lacking in the existing empirical subject-model based control.

Original languageEnglish (US)
Title of host publicationACC 2015 - 2015 American Control Conference
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages5782-5787
Number of pages6
ISBN (Electronic)9781479986842
DOIs
StatePublished - Jul 28 2015
Event2015 American Control Conference, ACC 2015 - Chicago, United States
Duration: Jul 1 2015Jul 3 2015

Publication series

NameProceedings of the American Control Conference
Volume2015-July
ISSN (Print)0743-1619

Other

Other2015 American Control Conference, ACC 2015
CountryUnited States
CityChicago
Period7/1/157/3/15

Fingerprint

Insulin
Model predictive control
Medical problems
Glucose
Blood
Simulators
Controllers

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering

Cite this

Wang, Q., Xie, J., Molenaar, P., & Ulbrecht, J. (2015). Model predictive control for type 1 diabetes based on personalized linear time-varying subject model consisting of both insulin and meal inputs: In Silico evaluation. In ACC 2015 - 2015 American Control Conference (pp. 5782-5787). [7172245] (Proceedings of the American Control Conference; Vol. 2015-July). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACC.2015.7172245
Wang, Qian ; Xie, Jinyu ; Molenaar, Peter ; Ulbrecht, Jan. / Model predictive control for type 1 diabetes based on personalized linear time-varying subject model consisting of both insulin and meal inputs : In Silico evaluation. ACC 2015 - 2015 American Control Conference. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 5782-5787 (Proceedings of the American Control Conference).
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Wang, Q, Xie, J, Molenaar, P & Ulbrecht, J 2015, Model predictive control for type 1 diabetes based on personalized linear time-varying subject model consisting of both insulin and meal inputs: In Silico evaluation. in ACC 2015 - 2015 American Control Conference., 7172245, Proceedings of the American Control Conference, vol. 2015-July, Institute of Electrical and Electronics Engineers Inc., pp. 5782-5787, 2015 American Control Conference, ACC 2015, Chicago, United States, 7/1/15. https://doi.org/10.1109/ACC.2015.7172245

Model predictive control for type 1 diabetes based on personalized linear time-varying subject model consisting of both insulin and meal inputs : In Silico evaluation. / Wang, Qian; Xie, Jinyu; Molenaar, Peter; Ulbrecht, Jan.

ACC 2015 - 2015 American Control Conference. Institute of Electrical and Electronics Engineers Inc., 2015. p. 5782-5787 7172245 (Proceedings of the American Control Conference; Vol. 2015-July).

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

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Wang Q, Xie J, Molenaar P, Ulbrecht J. Model predictive control for type 1 diabetes based on personalized linear time-varying subject model consisting of both insulin and meal inputs: In Silico evaluation. In ACC 2015 - 2015 American Control Conference. Institute of Electrical and Electronics Engineers Inc. 2015. p. 5782-5787. 7172245. (Proceedings of the American Control Conference). https://doi.org/10.1109/ACC.2015.7172245