Adaptive Control Design with Saturation Constraints for Different Experimental Glucose Models

Direct Model Reference Adaptive Control is an important algorithm that uses a linear combination of model states, the reference input, and the error between system and model outputs. Real applications are usually subject to limits on controlled variables for security or useful reasons. Due to the exclusive structure of the controller, several methods are developed to handle saturation constraints that cannot be applied directly to DMRAC. This article presents extensions of the algorithm to allow explicit processing of constraints. This research work considers the closed-loop control algorithm derived from the reference adaptive control model with saturation constraints, this control is applied for two models of glucose-insulin systems in the subject Type 1 Diabetes (T1D). The Bergman model and the long-term model are presented to study the dynamic behavior of glucose. In silico results of numerical simulation are provided to show the advantages of the proposed controllers.