Knowledge-based Closed-loop Control of Blood Glucose Concentration in Diabetic Patients and Comparison with H∞ Control Technique

Abstract

In this paper, fuzzy-based closed-loop controller is applied to obtain a robust controller for blood glucose regulation in type I diabetes mellitus patients. The control technique incorporates expert knowledge about treatment of disease by using Mamdani-type fuzzy logic controller to robustly stabilize the blood glucose concentration in normoglycemic level. Controller performance is considered in terms of its ability to reject the multiple meals, on an averaged nonlinear patient model. Robustness of the controller is tested over a group of patients with model parameter varying considerably from the average model. The controller provides the possibility of more accurate control of blood glucose level in the patient in spite of uncertainty in model parameters and measurement noise. The proposed controller has showed superiority over other classical control techniques. A comparative study is presented with well-known conventional H∞ control technique. Simulation results show the superiority of the proposed scheme in terms of reference tracking, disturbance rejection, and measurement noise in comparison with other approaches.