Linear Quadratic Gaussian-Based Closed-Loop Control of Type 1 Diabetes

We investigated the applicability of linear quadratic Gaussian (LQG) methodology to the subcutaneous blood glucose regulation problem. We designed an LQG-based feedback control algorithm using linearization of a previously published metabolic model of type 1 diabetes. A key feature of the controller...

Full description

Saved in:
Bibliographic Details
Published inJournal of diabetes science and technology Vol. 1; no. 6; pp. 834 - 841
Main Authors Patek, Stephen D., Breton, Marc D., Chen, Yuanda, Solomon, Chad, Kovatchev, Boris
Format Journal Article
LanguageEnglish
Published United States Diabetes Technology Society 01.11.2007
SeriesArtificial Pancreas: Closed-Loop Control of Glucose Variability in Diabetes
Subjects
Symposium
artificial pancreas
diabetes
LQG control
simulation
Online AccessGet full text
ISSN1932-2968
1932-3107
1932-3107
DOI10.1177/193229680700100606

Cover

More Information
Summary:We investigated the applicability of linear quadratic Gaussian (LQG) methodology to the subcutaneous blood glucose regulation problem. We designed an LQG-based feedback control algorithm using linearization of a previously published metabolic model of type 1 diabetes. A key feature of the controller is a Kalman filter used to estimate metabolic states of the patient based on continuous glucose monitoring. Insulin infusion is computed from linear quadratic regulator feedback gains applied to these estimates, generally seeking to minimize squared deviations from a target glucose concentration and basal insulin rate. We evaluated in silico subject-specific LQG control and compared it to preexisting proportional-integral-derivative control.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Funding: This work was funded in part through a grant from the Juvenile Diabetes Research Foundation Artificial Pancreas Project, Track 2.
ISSN:1932-2968
1932-3107
1932-3107
DOI:10.1177/193229680700100606