Embedded Model Predictive Control for a Wearable Artificial Pancreas.
Embedded Model Predictive Control for a Wearable Artificial Pancreas.
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DOI：
10.1109/tcst.2019.2939122
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发表时间：
2020-11
期刊：
影响因子：
--
通讯作者：
Dassau E
中科院分区：
文献类型：
--
作者：
Chakrabarty A;Healey E;Shi D;Zavitsanou S;Doyle FJ 3rd;Dassau E
虽然人工胰腺 (AP) 系统有望改善 1 型糖尿病 (T1DM) 患者的生活质量，但设计优化用户体验的便捷系统，尤其是对于那些生活方式积极的人，例如儿童和青少年，仍然是一个悬而未决的研究问题。在这项工作中，我们为 T1DM 患者介绍了 AP 系统模型预测控制 (MPC) 的嵌入式设计和实现，可显着减轻 AP 系统的重量和在身体上的足迹。 The embeddable controller is based on a zone MPC that has been evaluated in multiple clinical studies.所提出的嵌入式区域 MPC 的特点是成本函数中周期性安全区的设计更简单，并利用最先进的交替最小化算法来解决 MPC 固有的凸规划问题，并具有受凸约束的线性模型。 Off-line closed-loop data generated by the FDA-accepted UVA/Padova simulator is used to select an optimization algorithm and corresponding tuning parameters.通过资源有限的 Arduino Zero (Feather M0) 平台上的硬件在环计算机结果，我们展示了所提出的嵌入式 MPC 的潜力。尽管存在资源限制，但我们的嵌入式区域 MPC 在有/无用餐干扰补偿的情况下仍能实现与在 64 位桌面上实现的完整版本区域 MPC 相当的性能。绩效比较的指标包括正常血糖（[70, 180] mg/dL 范围）的中位百分比时间为 84.3%，对于已宣布的膳食为 83.1%，等效性测试得出 p = 0.0013；对于未宣布的膳食，则为 66.2% 与 66.0%，p = 0.0028。
While artificial pancreas (AP) systems are expected to improve the quality of life among people with type 1 diabetes mellitus (T1DM), the design of convenient systems that optimize the user experience, especially for those with active lifestyles, such as children and adolescents, still remains an open research question. In this work, we introduce an embeddable design and implementation of model predictive control (MPC) of AP systems for people with T1DM that significantly reduces the weight and on-body footprint of the AP system. The embeddable controller is based on a zone MPC that has been evaluated in multiple clinical studies. The proposed embedded zone MPC features a simpler design of the periodic safe zone in the cost function and the utilization of state-of-the-art alternating minimization algorithms for solving the convex programming problems inherent to MPC with linear models subject to convex constraints. Off-line closed-loop data generated by the FDA-accepted UVA/Padova simulator is used to select an optimization algorithm and corresponding tuning parameters. Through hardware-in-the-loop in silico results on a limited-resource Arduino Zero (Feather M0) platform, we demonstrate the potential of the proposed embedded MPC. In spite of resource limitations, our embedded zone MPC manages to achieve comparable performance of that of the full-version zone MPC implemented in a 64-bit desktop for scenarios with/without meal-disturbance compensations. Metrics for performance comparison included median percent time in the euglycemic ([70, 180] mg/dL range) of 84.3% vs. 83.1% for announced meals, with an equivalence test yielding p = 0.0013 and 66.2% vs. 66.0% for unannounced meals with p = 0.0028.
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影响因子：
4.2
作者：
Huyett LM;Dassau E;Zisser HC;Doyle FJ 3rd
通讯作者：
Doyle FJ 3rd
影响因子：
4.3
作者：
Dua, P.;Kouramas, K.;Pistikopoulos, E. N.
通讯作者：
Pistikopoulos, E. N.
影响因子：
16.2
作者：
Del Favero, Simone;Boscari, Federico;Bruttomesso, Daniela
通讯作者：
Bruttomesso, Daniela
影响因子：
5.8
作者：
Blauw, H.;van Bon, A. C.;DeVries, J. H.
通讯作者：
DeVries, J. H.
影响因子：
5
作者：
de Bock, Martin;Dart, Julie;Jones, Timothy
通讯作者：
Jones, Timothy