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

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• 作者：Ravi Gondhalekar ^{gondhalekar@seas.harvard.edu" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Eyal Dassau ^{dassau@seas.harvard.edu" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Francis J. Doyle III ^{frank_doyle@seas.harvard.edu" class="auth_mail" title="E-mail the corresponding author}Author Vitae
• 关键词：Model predictive control ; Periodic control ; Safety-critical control ; Artificial pancreas ; Type 1 diabetes mellitus
• 刊名：Automatica
• 出版年：2016
• 出版时间：September 2016
• 年：2016
• 卷：71
• 期：Complete
• 页码：237-246
• 全文大小：806 K

文摘

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.