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Periodic zone-MPC with asymmetric costs for outpatient-ready safety of an artificial pancreas to treat type 1 diabetes

机译:周期区带-MPC,用于人工胰腺治疗1型糖尿病的门诊安全性费用不对称

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摘要

A novel Model Predictive Control (MPC) law for an Artificial Pancreas (AP) to automatically deliver insulin to people with type 1 diabetes is proposed. The MPC law is an enhancement of the authors' zone-MPC approach that has successfully been trialled in-clinic, and targets the safe outpatient deployment of an AP. The MPC law controls blood-glucose levels to a diurnally time-dependent zone, and enforces diurnal, hard input constraints. The main algorithmic novelty is the use of asymmetric input costs in the MPC problem's objective function. This improves safety by facilitating the independent design of the controller's responses to hyperglycemia and hypoglycemia. The proposed controller performs predictive pump-suspension in the face of impending hypoglycemia, and subsequent predictive pump-resumption, based only on clinical needs and feedback. The proposed MPC strategy's benefits are demonstrated by in-silico studies as well as highlights from a US Food and Drug Administration approved clinical trial in which 32 subjects each completed two 25 h closed-loop sessions employing the proposed MPC law. (C) 2016 Elsevier Ltd. All rights reserved.
机译:提出了一种新颖的模型预测控制(MPC)律,用于人工胰腺(AP)自动向1型糖尿病患者输送胰岛素。 MPC法是对作者的区域-MPC方法的增强,该方法已在临床中成功试用,并针对AP的安全门诊部署。 MPC法将血糖水平控制在昼夜随时间变化的区域,并强制实施昼夜,严格的输入约束。算法上的新颖之处在于在MPC问题的目标函数中使用了不对称的输入成本。通过促进控制器对高血糖和低血糖反应的独立设计,可以提高安全性。提出的控制器仅在临床需要和反馈的情况下,在即将发生的低血糖情况下执行预测性泵浦暂停,并随后进行预测性泵浦恢复。拟议中的MPC策略的益处通过计算机模拟研究以及美国食品和药物管理局批准的临床试验证明,其中32名受试者均采用拟议的MPC法完成了两个25小时的闭环会议。 (C)2016 Elsevier Ltd.保留所有权利。

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