DocumentCode
184715
Title
MPC design for rapid pump-attenuation and expedited hyperglycemia response to treat T1DM with an Artificial Pancreas
Author
Gondhalekar, Ravi ; Dassau, Eyal ; Doyle, Francis J.
Author_Institution
Dept. of Chem. Eng., Univ. of California Santa Barbara (UCSB), Santa Barbara, CA, USA
fYear
2014
fDate
4-6 June 2014
Firstpage
4224
Lastpage
4230
Abstract
The design of a Model Predictive Control (MPC) strategy for the closed-loop operation of an Artificial Pancreas (AP) for treating Type 1 Diabetes Mellitus (T1DM) is considered in this paper. The contribution of this paper is to propose two changes to the usual structure of the MPC problems typically considered for control of an AP. The first proposed change is to replace the symmetric, quadratic input cost function with an asymmetric, quadratic function, allowing negative control inputs to be penalized less than positive ones. This facilitates rapid pump-suspensions in response to predicted hypoglycemia, while simultaneously permitting the design of a conservative response to hyperglycemia. The second proposed change is to penalize the velocity of the predicted glucose level, where this velocity penalty is based on a cost function that is again asymmetric, but additionally state-dependent. This facilitates the accelerated response to acute, persistent hyperglycemic events, e.g., as induced by unannounced meals. The novel functionality is demonstrated by numerical examples, and the efficacy of the proposed MPC strategy verified using the University of Padova/Virginia metabolic simulator.
Keywords
artificial organs; closed loop systems; diseases; patient treatment; predictive control; MPC design; MPC strategy; T1DM treatment; artificial pancreas; closed-loop operation; expedited hyperglycemia response; glucose level; model predictive control; negative control input; persistent hyperglycemic event; predicted hypoglycemia; quadratic input cost function; rapid pump-attenuation; rapid pump-suspension; type 1 diabetes mellitus; Cost function; Insulin; Pancreas; Predictive models; Sugar; Trajectory; Tuning; Biomedical; Control applications; Predictive control for linear systems;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference (ACC), 2014
Conference_Location
Portland, OR
ISSN
0743-1619
Print_ISBN
978-1-4799-3272-6
Type
conf
DOI
10.1109/ACC.2014.6859247
Filename
6859247
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