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Journal of Healthcare Engineering
Volume 5, Issue 1, Pages 1-22
Research Article

Adaptive Control of Artificial Pancreas Systems - A Review

Kamuran Turksoy1 and Ali Cinar1,2

1Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
2Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL, USA

Received 1 June 2013; Accepted 1 November 2013

Copyright © 2014 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Artificial pancreas (AP) systems offer an important improvement in regulating blood glucose concentration for patients with type 1 diabetes, compared to current approaches. AP consists of sensors, control algorithms and an insulin pump. Different AP control algorithms such as proportional-integral-derivative, model-predictive control, adaptive control, and fuzzy logic control have been investigated in simulation and clinical studies in the past three decades. The variability over time and complexity of the dynamics of blood glucose concentration, unsteady disturbances such as meals, time-varying delays on measurements and insulin infusion, and noisy data from sensors create a challenging system to AP. Adaptive control is a powerful control technique that can deal with such challenges. In this paper, a review of adaptive control techniques for blood glucose regulation with an AP system is presented. The investigations and advances in technology produced impressive results, but there is still a need for a reliable AP system that is both commercially viable and appealing to patients with type 1 diabetes.