摘要：The properties of an objective function are fundamental to the functionality of a model predictive controller (MPC). In automated glucose control, avoidance of hypo- and hyperglycemia introduces significant challenges in the design of this cost function. We present a new formulation of the cost function for an MPC based on clinical requirements, and validate the algorithm under in silico and advisory mode assessments. The proposed formulation exhibits significant improvements in avoiding hypoglycemia, compared to clinically validated controllers, and can also mitigate hyperglycemia, across a wide range of in silico scenarios as well as glucose responses seen in actual clinical settings.
