On‐line adaptive algorithm with glucose prediction capacity for subcutaneous closed loop control of glucose: evaluation under fasting conditions in patients with Type 1 diabetes

Abstract

The MPC algorithm is suitable for glucose control during fasting within an extracorporeal artificial beta-cell in the subcutaneous route Type 1 diabetic patients.

A run-to-run control strategy to adjust basal insulin infusion rates in type 1 diabetes

“…This is introduced by replacing I(t) in equation 9 with I ′(t) as given by (10) where the modulating gain k m (t) is given, in the Lapalce domain, by (11) with the input k p (t) being a step profile corresponding to the desired gain for each segment. Given that the model is now time-varying with respect to time of day, t = 0 is set to correspond to midnight.…”

“…There have been multiple algorithms proposed for closed-loop control of glycemia, including MPC [7]- [10], PD [11]- [13], PID [14]- [17], and H ∞ [18], [19] -for a recent review of the literature in this area see [20]. All of these controllers are based on the assumption that a continuous glucose sensor is available, and although sensor technology has improved significantly over the last few years, it is still short of the reliability and accuracy required for commercial implementation of such a closed-loop system [20].…”

Hypoglycemia Prevention in Closed-Loop Artificial Pancreas for Patients with Type 1 Diabetes

“…In ), the system was tested in a clinical study with children and adolescents. Earlier version of this MPC algorithm was tested in previous clinical study to evaluate its control and prediction performance during fasting conditions (Shaller et al (2006)). An automated closed-loop insulin delivery system was tested in a multinational clinical trial (Bruttomesso et al (2009);Clarke et al (2009)).…”

A feedforward–feedback glucose control strategy for type 1 diabetes mellitus

“…In recent years, model-based control strategies such as model predictive control (MPC), adaptive control [6,[13][14][15][16][17][18], optimal control [19], neural networks [20,21], and H-infinity control [22,23], have been proposed and evaluated in simulation studies. A few experimental applications of MPC have also been reported [16,17,24]. Glucose control strategies can be updated on an infrequent basis (e.g., daily) using a "run-to-run" control approach [25,26].…”

“…A PID control strategy is attractive for glucose control because it mimics the first and second phase responses that the pancreas beta cells use to secrete insulin in response for non-diabetic individuals to the continuously sensed glucose [9]. In recent years, model-based control strategies such as model predictive control (MPC), adaptive control [6,[13][14][15][16][17][18], optimal control [19], neural networks [20,21], and H-infinity control [22,23], have been proposed and evaluated in simulation studies. A few experimental applications of MPC have also been reported [16,17,24].…”