Neural inverse optimal control applied to type 1 diabetes mellitus patients

This paper deals with blood glucose level control. Inverse optimal trajectory tracking via control Lyapunov function for discrete time non-linear systems is applied. The control law calculates the subcutaneous insulin delivery rate in order to prevent hyperglycemia and hypoglycemia levels. For this paper, a quadratic candidate CLF is used to synthesize the inverse optimal control law. The proposed algorithm is tuned to follow a desired trajectory; this trajectory reproduces the glucose absorption of a healthy person. Simulation results illustrate the applicability of the control law.