速度加权预防控制者在治疗T1DM的人工胰腺MPC中引起的低血糖。

Ravi Gondhalekar, Eyal Dassau, Francis J Doyle
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引用次数: 19

摘要

研究了人工胰腺(AP)治疗1型糖尿病的闭环手术模型预测控制(MPC)策略。本文的贡献在于在MPC问题的成本函数中提出了一种速度加权机制,该机制有助于根据预测的血糖水平变化率来惩罚预测的高血糖血糖偏差。该方法为控制设计者提供了一定的自由度,以独立地塑造AP对高血糖漂移的上坡和下坡反应;本文特别强调的是下坡响应。该提案旨在解决在大范围高血糖活动(例如餐后)后控制器诱导的低血糖的危险问题,这部分是由于皮下葡萄糖传感和皮下胰岛素输注的大量延迟造成的-这里考虑的情况。使用弗吉尼亚大学/帕多瓦代谢模拟器演示了该方法的有效性,包括未通知和通知的用餐场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Velocity-weighting to prevent controller-induced hypoglycemia in MPC of an artificial pancreas to treat T1DM.

The design of a Model Predictive Control (MPC) strategy for the closed-loop operation of an Artificial Pancreas (AP) to treat type 1 diabetes mellitus is considered. The contribution of this paper is to propose a velocity-weighting mechanism, within an MPC problem's cost function, that facilitates penalizing predicted hyperglycemic blood-glucose excursions based on the predicted blood-glucose levels' rates of change. The method provides the control designer some freedom for independently shaping the AP's uphill versus downhill responses to hyperglycemic excursions; of particular emphasis in this paper is the downhill response. The proposal aims to tackle the dangerous issue of controller-induced hypoglycemia following large hyperglycemic excursions, e.g., after meals, that results in part due to the large delays of subcutaneous glucose sensing and subcutaneous insulin infusion - the case considered here. The efficacy of the proposed approach is demonstrated using the University of Virginia/Padova metabolic simulator with both unannounced and announced meal scenarios.

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