複数の食事シナリオに対応可能な血糖値のTube-basedモデル予測制御

抄録

This paper aims to keep blood glucose levels within an acceptable range for any prior announced meal scenarios by a model predictive control approach. However, due to the nonlinearity of the system and the necessity to set decision variables for each meal scenario, a straightforward formulation of a mathematical optimization problem to determine insulin dose becomes a nonlinear optimization problem with many decision variables. To formulate the mathematical optimization problem as a convex quadratic programming problem, we approximate the nonlinear system with a linear one and apply a tube method by considering the linearization error as a disturbance. Furthermore, we suppress the increase in blood glucose levels due to meals by discrete-time LQ control for systems with exogenous inputs, which makes the number of decision variables independent of the number of the meal scenarios.