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首页> 外文期刊>IFAC PapersOnLine >Extremum Seeking Control Based Zone Adaptation for Zone Model Predictive Control in Type 1 Diabetes * * This work is supported by the National Institutes of Health Grants DP3DK094331, DP3DK104057 and UC4DK108483.
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Extremum Seeking Control Based Zone Adaptation for Zone Model Predictive Control in Type 1 Diabetes * * This work is supported by the National Institutes of Health Grants DP3DK094331, DP3DK104057 and UC4DK108483.

机译：基于极端寻求控制的区域适应性用于1型糖尿病区域模型预测控制 * * 这项工作得到了美国国家研究所的支持健康补助金DP3DK094331，DP3DK104057和UC4DK108483。

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摘要

Clinical trials have demonstrated that zone model predictive control is an effective closed-loop blood glucose regulation method for people with type 1 diabetes (T1D). This paper presents a universal model-free optimization method to seek an optimal zone for T1D patients individually. A clinical glycemic risk index named relative regularized glycemic penalty index (rrGPI) is used as the cost function. The proposed method is based on extremum seeking control that uses only the rrGPI index, calculated from measurements by a continuous glucose monitor, to update a controller’s blood glucose target zone’s upper bound and lower bound simultaneously. The method proposed uses a decaying feedback gain and a vanishing dither signal to improve the extremum seeking controller’s robustness against various uncertainties. In silico trials suggest that the proposed method is able to converge to the personalized optimal zone in less than a week of adaptation. In a 30-day in silico trial, the time spent in the range [70,180] mg/dL is increased by about 3% and 2% for unannounced 60 gCHO ( grams of carbohydrates ) and 90 gCHO meals, respectively, compared to the zone [80,140] mg/dL employed in the authors’ current zone controller.
机译：临床试验表明，区域模型预测控制是1型糖尿病（T1D）患者的有效闭环血糖调节方法。本文提出了一种通用的无模型优化方法，可以单独为T1D患者寻找最佳区域。名为相对正规化血糖罚分指数（rrGPI）的临床血糖风险指数被用作成本函数。拟议的方法基于极值搜索控制，该控制仅使用rrGPI指数（由连续血糖监测仪的测量结果计算得出）来同时更新控制器的血糖目标区域的上限和下限。提出的方法使用衰减的反馈增益和消失的抖动信号来提高极值搜索控制器针对各种不确定性的鲁棒性。计算机模拟试验表明，所提出的方法能够在不到一周的适应时间内收敛到个性化的最佳区域。在30天的计算机模拟试验中，与区域相比，未宣布的60 gCHO（碳水化合物）和90 gCHO餐所花费的时间分别为[70,180] mg / dL分别增加了约3％和2％作者的当前区域控制器采用了[80,140] mg / dL。

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