An Extended Static and Dynamic Feedback-Feedforward Control Algorithm for Insulin Delivery in the Control of Blood Glucose Level

The potential for successful automatic control of blood glucose concentration (BGC) has entered a new era because of recent technological advancements in insulin pumps and blood glucose sensors. However, a critical advancement necessary for full automation and long-term use is a control algorithm that can effectively maintain tight control of BGC under extreme variation of important disturbances such as activity, stress, and food consumption. Because feedforward control (FFC) models disturbances directly, it has the potential to eliminate the effects of disturbances completely. A Wiener-type feedforward control law is limited to the inclusion of only input (i.e., modeled disturbances and the manipulated variable) dynamics. Using a semicoupled modeling network that includes pseudo-blood insulin concentration, this work presents a more phenomenological FFC law that includes input dynamics, blood insulin and blood glucose dynamics, and blood glucose levels. Modeling results on 15 adults with type 1 diabetes mellitus for the proposed method are nearly identical to Wiener modeling results.