NDLI: Receding Horizon Control of type I diabetes based on a data-driven linear time-varying state-space model

Content Provider	IEEE Xplore Digital Library
Author	Jing Zhou Qian Wang Molenaar, P. Ulbrecht, J. Gold, C. Rovine, M.
Copyright Year	2010
Description	Author affiliation: Dept. of Mech. & Nucl. Eng., Penn State Univ., University Park, PA, USA (Jing Zhou; Qian Wang) \|\| Dept. of Human Dev. & Family Studies, Penn State Univ., University Park, PA, USA (Molenaar, P.; Rovine, M.) \|\| Penn State Gerontology Center, Penn State Univ., University Park, PA, USA (Gold, C.) \|\| Dept. of Biobehavioral Health & Med., Penn State Univ., University Park, PA, USA (Ulbrecht, J.)
Abstract	In this paper, we consider the problem of blood glucose control for type 1 diabetic patients. In particular, we focus on developing control algorithms for an Artificial Pancreas which is a portable or implantable automated insulin delivery system composed of a continuous glucose monitor, an insulin pump, and a control law that links the measured blood glucose concentration and insulin delivery. We have designed Receding Horizon Control (RHC) (which is also known as the Model Predictive Control) for two specific patients, respectively, based on a data-driven linear time-varying state-space model developed in for each patient using clinical data. The control parameters are tuned specifically for each patient. For patient 1, the RHC algorithm performs well with no information (e.g., amount and time) of meal intake, which results in the so-called feedback alone control. For patient 2, information of meal intake is necessary for the RHC algorithm to reach acceptable closed-loop performance, which results in the so-called feedback plus feedforward control. For both patients, we evaluate the performance of the RHC designs via simulation and compare the simulation results with clinical data. We also test the robustness of the RHC design with respect to estimation errors in the amount of carbohydrate content (CHO) of the meal.
Starting Page	2033
Ending Page	2038
File Size	844022
Page Count	6
File Format	PDF
ISBN	9781424474264
ISSN	07431619
e-ISBN	9781424474271
DOI	10.1109/ACC.2010.5531641
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-06-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	American Automatic Control Council(AACC)
Subject Keyword	Diabetes Automatic control Sugar Insulin Blood Control systems Predictive models Feedback Pancreas Patient monitoring
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering

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