Abstract This work presents a pulsatile Zone Model Predictive Control (pZMPC) for the control of blood glucose concentration (BGC) in patients with Type 1 Diabetes Mellitus (T1DM). The main novelties of the algorithm – in contrast to other existing strategies – are: (i) it controls the patient glycemia by injecting short duration insulin boluses for both, the basal and bolus infusions, in an unified manner, (ii) it performs the predictions and estimations (critical to anticipate both, hypo and hyperglycemia) based on a physiological individualized long-term model, (iii) it employs disturbance observers to compensate plant-model mismatches, (iv) it ensures, under standard assumptions, closed-loop stability, and (v) it can be used – under minor modifications – as an optimal basal–bolus calculator to emulate conventional therapies. Because of the latter characteristic, a significantly better performance is achieved, not only in terms of classical indexes (time in the normoglycemia zone, avoidance of hypoglycemia in the short term, avoidance of hyperglycemia in the long term) but also in terms of its applicability (use of the pump or injections). Such a performance is tested in a cohort of in-silico patients from the FDA-accepted UVA/Padova simulation platform, considering the most challenging scenarios.

中文翻译：

---

稳定脉动 MPC 下的人工胰腺：提高闭环性能

摘要 这项工作提出了一种用于控制 1 型糖尿病 (T1DM) 患者血糖浓度 (BGC) 的脉动区模型预测控制 (pZMPC)。与其他现有策略相比，该算法的主要新颖之处在于：（i）它通过以统一的方式为基础和推注注射短时间胰岛素推注来控制患者血糖，（ii）它执行基于生理个体化长期模型的预测和估计（对于预测低血糖和高血糖至关重要），（iii）它使用干扰观察器来补偿植物模型的不匹配，（iv）它确保在标准假设下闭环稳定性，以及 (v) 它可以在稍作修改后用作模拟常规疗法的最佳基础推注计算器。由于后一个特性，不仅在经典指标（在正常血糖区的时间，短期内避免低血糖，长期避免高血糖）方面而且在其适用性方面都实现了明显更好的性能（使用泵或注射）。考虑到最具挑战性的场景，这种性能在来自 FDA 接受的 UVA/Padova 模拟平台的一组硅片患者中进行了测试。