Adaptive Zone Model Predictive Control of Artificial Pancreas Based on Glucose- and Velocity-Dependent Control Penalties.

ABSTRACT:

Objective

Zone model predictive control (MPC) has been proven to be an efficient approach to closed-loop insulin delivery in clinical studies. In this paper, we aim to safely reduce mean glucose levels by proposing control penalty adaptation in the cost function of zone MPC.

Methods

A zone MPC method with a dynamic cost function that updates its control penalty parameters in real time according to the predicted glucose and its rate of change is developed. The proposed method is evaluated on the entire 100-adult cohort of the FDA-accepted UVA/Padova T1DM simulator and compared with the zone MPC tested in an extended outpatient study.

Results

For unannounced meals, the proposed method leads to statistically significant improvements in terms of mean glucose (153.8 mg/dL

SUBMITTER: Shi D 

PROVIDER: S-EPMC6760658 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature