Bequette B Wayne, Cameron Faye, Baysal Nihat, Howsmon Daniel P, Buckingham Bruce A, Maahs David M, Levy Carol J
Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, 110 Eighth St., Troy, NY 12180-3590, USA.
Stanford University, 780 Welch Road, CJ320H MC 5776, Palo Alto, CA 94304, USA.
Processes (Basel). 2016 Dec;4(4). doi: 10.3390/pr4040039. Epub 2016 Oct 18.
The development of a closed-loop artificial pancreas to regulate the blood glucose concentration of individuals with type 1 diabetes has been a focused area of research for over 50 years, with rapid progress during the past decade. The daily control challenges faced by someone with type 1 diabetes include asymmetric objectives and risks, and one-sided manipulated input action with frequent relatively fast disturbances. The major automation steps toward a closed-loop artificial pancreas include (i) monitoring and overnight alarms for hypoglycemia (low blood glucose); (ii) overnight low glucose suspend (LGS) systems to prevent hypoglycemia; and (iii) fully closed-loop systems that adjust insulin (and perhaps glucagon) to maintain desired blood glucose levels day and night. We focus on the steps that we used to develop and test a probabilistic, risk-based, model predictive control strategy for a fully closed-loop artificial pancreas. We complete the paper by discussing ramifications of lessons learned for chemical process systems applications.
五十多年来，开发用于调节1型糖尿病患者血糖浓度的闭环人工胰腺一直是一个重点研究领域，在过去十年中取得了迅速进展。1型糖尿病患者每天面临的控制挑战包括不对称的目标和风险，以及具有频繁相对快速干扰的单边操纵输入动作。迈向闭环人工胰腺的主要自动化步骤包括：（i）监测和夜间低血糖（低血糖）警报；（ii）夜间低血糖暂停（LGS）系统以预防低血糖；以及（iii）全天调节胰岛素（可能还有胰高血糖素）以维持所需血糖水平的全闭环系统。我们重点关注用于开发和测试全闭环人工胰腺的基于概率、风险的模型预测控制策略的步骤。我们通过讨论从化学过程系统应用中学到的经验教训的影响来完成本文。
