1型糖尿病胰岛素输送的收缩模型预测控制

A. Grancharova, Ivana Valkova
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引用次数: 1

摘要

本文提出了一种基于非线性血糖-胰岛素动力学模型的低复杂度非线性模型预测控制(NMPC)方法。在NMPC问题的表述中引入了收缩约束的思想,保证了小预测视界下闭环系统的稳定性。特别考虑了超前一步的NMPC问题。进一步,提出了一种拟nmpc方法,该方法基于非线性系统动力学的顺序线性化,并找到由此产生的凸二次约束二次规划问题的次优解。建议的方法适合嵌入到自动血糖控制系统中,因为它将降低在线NMPC计算的复杂性,简化软件实现,并减少对可用内存的要求。通过对葡萄糖-胰岛素动力学非线性模型的仿真,说明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Contractive Model Predictive Control for Insulin Delivery for Type 1 Diabetics
In this paper, a low complexity nonlinear model predictive control (NMPC) approach to blood glucose control is suggested, which is based on the nonlinear glucose-insulin dynamics model. It applies the idea of introducing a contractive constraint in the NMPC problem formulation, which would guarantee the closed-loop system stability when using a small prediction horizon. Particularly, the one step ahead NMPC problem is considered. Further, a quasi-NMPC method is developed, which is based on a sequential linearization of the nonlinear system dynamics and finding a suboptimal solution of the resulting convex Quadratically Constrained Quadratic Programming problem. The suggested approach would be appropriate to be embedded in an automatic blood glucose control system, since it will reduce the complexity of the on-line NMPC computations, simplify the software implementation, and reduce the requirements for available memory. The proposed method is illustrated with simulations on the nonlinear model of glucose-insulin dynamics.
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