Annu Int Conf IEEE Eng Med Biol Soc. 2022 Jul;2022:171-176. doi: 10.1109/EMBC48229.2022.9871264.
Currently, continuous glucose monitoring sensors are used in the artificial pancreas to monitor blood glucose levels. However, insulin and glucagon concentrations in different parts of the body cannot be measured in real-time, and determining body glucagon sensitivity is not feasible. Estimating these states provides more information about the current system status, facilitating improved decision-making by the model-based controller. In this regard, the aim of this paper is to design a nonlinear high-gain observer for a bi-hormonal artificial pancreas in the presence of measurement noises, model uncertainties, and disturbances. The model used in the observer is based on an existing intraperitoneal nonlinear animal model in the literature. This model is modified by assuming that insulin can directly transfer from the peritoneal cavity to the bloodstream. Based on a set of realistic assumptions, one model is considered after each hormone infusion, and two observers are separately designed. The model is divided into the insulin-phase and glucagon-phase models based on a set of realistic assumptions. Thereafter, two high-gain observers are designed separately for these phases contributing to estimating the non-measurable states. The observer error is proven to be locally uniformly ultimately bounded, and it is verified that any asymptotically stable control laws remain stable in the presence of the observer. The performance of the observers with different gains is evaluated for a scenario with multiple insulin and glucagon infusions. The proposed observer converges to a finite error, according to the results. Clinical relevance- In Type 1 diabetic patients, the developed observer can be employed in a closed-loop artificial pan-creas to improve the performance of model-based controllers. It estimates the key states, which are necessary for forecasting the body's response to insulin and glucagon boluses.
目前,连续血糖监测传感器被用于人工胰腺中以监测血糖水平。然而,身体不同部位的胰岛素和胰高血糖素浓度无法实时测量,并且确定身体胰高血糖素敏感性是不可行的。估计这些状态可以提供有关当前系统状态的更多信息,从而有助于基于模型的控制器做出更好的决策。在这方面,本文的目的是设计一种在存在测量噪声、模型不确定性和干扰的情况下用于双激素人工胰腺的非线性高增益观测器。观测器中使用的模型基于文献中现有的腹腔内非线性动物模型。通过假设胰岛素可以直接从腹腔转移到血液中来修改该模型。基于一组现实的假设,在每次激素输注后考虑一个模型,并分别设计两个观测器。该模型根据一组现实的假设分为胰岛素相和胰高血糖素相模型。此后,分别为这些阶段设计两个高增益观测器,有助于估计不可测量的状态。观测器误差被证明是局部一致最终有界的,并且验证了在存在观测器的情况下任何渐近稳定的控制律仍然是稳定的。对于具有多种胰岛素和胰高血糖素输注的场景,评估了具有不同增益的观测器的性能。根据结果,所提出的观测器收敛到有限的误差。临床相关性- 在 1 型糖尿病患者中,开发的观测器可以用于闭环人工胰腺中,以提高基于模型的控制器的性能。它估计了关键状态,这些状态对于预测身体对胰岛素和胰高血糖素脉冲的反应是必要的。