scholarly journals Periodic-Zone Model Predictive Control for Diurnal Closed-Loop Operation of an Artificial Pancreas

2013 ◽  
Vol 7 (6) ◽  
pp. 1446-1460 ◽  
Author(s):  
Ravi Gondhalekar ◽  
Eyal Dassau ◽  
Howard C. Zisser ◽  
Francis J. Doyle
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Closed Loop ◽  
Artificial Pancreas ◽  
Zone Model

scholarly journals Outpatient Closed-Loop Control with Unannounced Moderate Exercise in Adolescents Using Zone Model Predictive Control

2017 ◽  
Vol 19 (6) ◽  
pp. 331-339 ◽  
Author(s):  
Lauren M. Huyett ◽  
Trang T. Ly ◽  
Gregory P. Forlenza ◽  
Suzette Reuschel-DiVirgilio ◽  
Laurel H. Messer ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Closed Loop ◽  
Zone Model ◽  
Closed Loop Control ◽  
Moderate Exercise ◽  
Loop Control

scholarly journals Clinical Evaluation of an Automated Artificial Pancreas Using Zone-Model Predictive Control and Health Monitoring System

2014 ◽  
Vol 16 (6) ◽  
pp. 348-357 ◽  
Author(s):  
Rebecca A. Harvey ◽  
Eyal Dassau ◽  
Wendy C. Bevier ◽  
Dale E. Seborg ◽  
Lois Jovanovič ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Monitoring System ◽  
Predictive Control ◽  
Clinical Evaluation ◽  
Health Monitoring ◽  
Artificial Pancreas ◽  
Zone Model ◽  
Health Monitoring System

scholarly journals Application of Zone Model Predictive Control Artificial Pancreas During Extended Use of Infusion Set and Sensor: A Randomized Crossover-Controlled Home-Use Trial

Diabetes Care ◽  
2017 ◽  
Vol 40 (8) ◽  
pp. 1096-1102 ◽  
Author(s):  
Gregory P. Forlenza ◽  
Sunil Deshpande ◽  
Trang T. Ly ◽  
Daniel P. Howsmon ◽  
Faye Cameron ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Artificial Pancreas ◽  
Zone Model

scholarly journals A Closed-Loop Artificial Pancreas Using Model Predictive Control and a Sliding Meal Size Estimator

2009 ◽  
Vol 3 (5) ◽  
pp. 1082-1090 ◽  
Author(s):  
Hyunjin Lee ◽  
Bruce A. Buckingham ◽  
Darrell M. Wilson ◽  
B. Wayne Bequette
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Closed Loop ◽  
Artificial Pancreas ◽  
Estimation Algorithm ◽  
Substantial Improvement ◽  
Performance Comparison ◽  
Diabetic Subject ◽  
Meal Size ◽  
Size Estimation

The objective of this article is to present a comprehensive strategy for a closed-loop artificial pancreas. A meal detection and meal size estimation algorithm is developed for situations in which the subject forgets to provide a meal insulin bolus. A pharmacodynamic model of insulin action is used to provide insulin-on-board constraints to explicitly include the future effect of past and currently delivered insulin boluses. In addition, a supervisory pump shut-off feature is presented to avoid hypoglycemia. All of these components are used in conjunction with a feedback control algorithm using model predictive control (MPC). A model for MPC is developed based on a study of 20 subjects and is tested in a hypothetical clinical trial of 100 adolescent and 100 adult subjects using a Food and Drug Administration-approved diabetic subject simulator. In addition, a performance comparison of previously and newly proposed meal size estimation algorithms using 200 in silico subjects is presented. Using the new meal size estimation algorithm, the integrated artificial pancreas system yielded a daily mean glucose of 138 and 132 mg/dl for adolescents and adults, respectively, which is a substantial improvement over the MPC-only case, which yielded 159 and 145 mg/dl.

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