Artificial pancreas (AP) systems have shown to improve glucose regulation in type 1 diabetes (T1D) patients. However, full closed-loop performance remains a challenge particularly in children and adolescents, since these age groups often present the worst glycemic control. In this work, an algorithm based on switched control and time-varying IOB constraints is presented. The proposed control strategy is evaluated in silico using the FDA-approved UVA/ Padova simulator and its performance contrasted with the previously introduced Automatic Regulation of Glucose (ARG) algorithm in the pediatric population. The effect of unannounced meals is also explored. Results indicate that the proposed strategy achieves lower hypo- and hyperglycemia than the ARG for both announced and unannounced meals.

Block diagram and illustrative example of insulin and glucose evolution over time for the proposed algorithm (ARGAE)

人工胰腺（AP）系统已显示可改善1型糖尿病（T1D）患者的血糖调节。然而，特别是在儿童和青少年中，全面的闭环性能仍然是一个挑战，因为这些年龄组的血糖控制最差。在这项工作中，提出了一种基于切换控制和时变IOB约束的算法。拟议的控制策略是使用FDA批准的UVA / Padova仿真器在计算机上进行评估的，其性能与先前在儿科人群中引入的葡萄糖自动调节（ARG）算法形成对比。还探讨了未进餐的影响。结果表明，对于已宣布和未宣布的进餐，所提出的策略可实现比ARG更低的低血糖和高血糖。

提出的算法（ARGAE）的胰岛素和葡萄糖随时间演变的框图和说明性示例