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Automatically estimated meals in Model Predictive Control-Moving Horizon Estimation control strategy

文献类型: 会议论文

第一作者: Máté Siket

作者: Máté Siket 1 ; Kamilla Novák 2 ; Levente Kovács 3 ; Gy?rgy Eigner 3 ;

作者机构: 1.Physiological Controls Research Center, óbuda University|Institute for Computer Science and Control, Budapest, Hungary|Applied Informatics and Applied Mathematics Doctoral School, óbuda University, Budapest

2.Physiological Controls Research Center, óbuda University

3.Physiological Controls Research Center, óbuda University|Biomatics and Applied Artificial Intelligence Institute, John von Neumann Faculty of Informatics, óbuda University

关键词: Uncertainty;Estimation;Predictive models;Glucose;Pancreas;Noise measurement;Blood

会议名称: Asian Control Conference

主办单位:

页码: 1367-1372

摘要: Current artificial pancreas systems rely on the carbohydrate counting of the patients. This article investigates the carbohydrate estimation possibility in a model predictive control (MPC) - moving horizon estimation (MHE) strategy. Errors in the meal estimations are evaluated based on the 1-step-ahead prediction accuracy of the controller, to examine the short-term validity of the estimated parameters. The effect of the sensor noise and the available number of measurements are also taken into account. The results suggest that it is able to achieve or surpass the carbohydrate counting accuracy of the patients in an MPCMHE control strategy if a sufficient number of measurements are available. Depending on the time passed since the consumption of the meal, under- or overestimation of the time constant can have the opposite effect on the blood glucose prediction.

分类号: tp273-53

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