New efforts have been made to build up prototypes of subcutaneous closed-loop systems for controlling blood glucose (BG) levels in type I diabetes mellitus (TIDM) patients with the development of clinically accurate continuous glucose monitors, automated micro-insulin dispenser (MID), and control algorithms. There is an urgency to develop new control algorithm to determine the desired dose of insulin for maintaining normal BG levels. As a solution to the above issue, a novel backstepping sliding mode Gaussian controller (BSMGC) is proposed whose gains vary dynamically with respect to the error signal. A feedback control law is formulated by a hybrid approach based on BSMGC. A ninth-order linearized state-space model of a nonlinear TIDM patient with the MID is formulated for the design of the BSMGC. This controller is evaluated, and the results are compared with other recently published control techniques. The output responses clearly reveal the better performance of the proposed method to control the BG level within the range of normoglycaemia in terms of accuracy, robustness and handling uncertainties.
During the past few decades, optimal control of Blood Glucose (BG) concentration with adequate feedback loop has been of ample importance for Type-I Diabetes Mellitus (TIDM) patients as far as an Artificial Pancreas (AP) realization is concerned. Now-a-days, in addition to the BG control, the design of the Micro-Insulin Dispenser (MID) with a robust control algorithm to regulate the other chronic clinical disorders based on prolonged medications is also quite indispensable. A novel Kalman Filtering Model Predictive Controller (KFMPC) has been proposed in this current work to solve the aforementioned problem. For designing of the KFMPC, a 9th order state-space model of the TIDM patient with MID is considered. In this control strategy, the Conventional Model Predictive Controller (CMPC) is re-formulated with a state estimator based on the Kalman filtering methodology to improve the control execution. The justification of enhanced control performance of KFMPC is demonstrated by comparative result analysis with other published control techniques. The simulations are carried out through MATLAB/SIMULINK environment and the results indicate comparatively better control ability of the suggested algorithm to control the BG level within the normoglycaemic range (70 - 120mg/dl) as far as accuracy, stability, quick damping and robustness.
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