A Closed-Loop Artificial Pancreas Using a Proportional Integral Derivative with Double Phase Lead Controller Based on a New Nonlinear Model of Glucose Metabolism

Abstract

The linear controller presented, based on the linearization of a new easily identifiable nonlinear model, achieves good glucose control with low exposure to hypoglycemia and hyperglycemia.

Multicenter Closed-Loop Insulin Delivery Study Points to Challenges for Keeping Blood Glucose in a Safe Range by a Control Algorithm in Adults and Adolescents with Type 1 Diabetes from Various Sites

“…The missing link between CSII and CGM is the control algorithm that will drive insulin delivery according to patient needs at all times so that blood glucose can be kept in a near-normal range with minimal patient intervention. Encouraging pilot results have been reported using proportional-integral-derivative control, [3][4][5][6] model predictive control (MPC), [7][8][9] and fuzzy logic control 10 strategies applied to limited numbers of patients. Whereas most studies achieved safe and effective control overnight, the control of glucose in postmeal periods appeared quite challenging.…”

Clinical Results of an Automated Artificial Pancreas Using Technosphere Inhaled Insulin to Mimic First-Phase Insulin Secretion

“…Intensive glycemic control in type 1 diabetes has been shown to reduce the incidence and progression of microvascular and macrovascular complications. 1,2 One validated way to improve glycemic control is the use of insulin pumps and/or continuous glucose monitors (CGMs). 3-5 However, many patients do not wear or manage the devices optimally 6-9 and clinical penetration is far from complete, even in the top clinical centers.…”

In-silico Testing of a Generalized Predictive Control Based Artificial Pancreas for Child Patients with Type 1 Diabetes

“…It is comparable with several other controllers tested with T1DMS. For example, the BGC percentage within the euglycemic range of in-silico subjects with the PIDD, PID and MPC controllers was 77%, 72.6% and 79.6%, respectively [10,11]. Therefore, the GPC+ARGT+ASF controller was effective and can be potentially applied in the AP systems.…”

“…At present, several control algorithms have been applied to the intelligent controller of AP systems, including proportional-integral-derivative (PID) control, model predictive control (MPC) and generalized predictive control (GPC) et al [6][7][8][9][10][11][12]. GPC has received a lot of attention in the past few years because it is fairly robust and can be easily implemented [13][14][15].…”