Nonlinear model predictive control for an artificial β-cell

Abstract

In this contribution we apply receding horizon constrained nonlinear optimal control to the computation of insulin administration for people with type 1 diabetes. The central features include a multiple shooting algorithm based on sequential quadratic programming (SQP) for optimization and an explicit Dormand-Prince Runge-Kutta method (DOPRI54) for numerical integration and sensitivity computation. The study is based on a physiological model describing a virtual subject with type 1 diabetes. We compute the optimal insulin administration in the cases with and without announcement of the meals (the major disturbances). These calculations provide practical upper bounds on the quality of glycemic control attainable by an artificial β-cell. © 2010 Springer -Verlag Berlin Heidelberg.