Terminal Synergetic and State Feedback Linearization Based Controllers for Artificial Pancreas in Type 1 Diabetic Patients

Abstract

Lack of insulin production by pancreas causes high blood glucose level (BGL) in the diabetic patients. For their treatment, manual insulin intake is possible only during the day timings but not feasible during the night when the patient is sleeping. Artificial pancreas (AP) is used for the automatic regulation of BGL by continuous injection of insulin. The nonlinear Bergman's Minimal Model (BMM) considers fixed meal disturbance which may actually vary continuously during medication due to meal intake or by doing exercise. This variation has been taken into account by the Extended Bergman's Minimal Model (EBMM). In this paper, two nonlinear: Terminal Synergetic and State Feedback Linearization based controllers have been proposed for AP to regulate BGL using EBMM. Asymptotic stability of the proposed controllers has been proved using Lyapunov theory. Comparison of the proposed controllers with each other and that with PID controller has been done using MATLAB/Simulink. White noise has been added as the disturbance to further analyze the output performance of the proposed controllers. The Terminal Synergetic controller which performs better than others, has also been implemented on the data of six Type 1 diabetic patients available in the literature.

Terminal Synergetic Control for Plate Heat Exchanger

“…Terminal synergetic control (TSC) is the enhanced control method in terms of improving convergence while maintaining the beneficial characteristics of the SC approach [21,[28][29][30][31]. In the TSC method, both macro variables which are a function of an error, and/or the corresponding dynamic evolutions are selected so that the finite time convergence of the macro variables and errors are satisfied [21,28,29,[32][33][34][35][36][37]. The TSC method has been implemented in various applications in previous literature [21,[28][29][30][31][32][33][34][35][36][37].…”

“…In the TSC method, both macro variables which are a function of an error, and/or the corresponding dynamic evolutions are selected so that the finite time convergence of the macro variables and errors are satisfied [21,28,29,[32][33][34][35][36][37]. The TSC method has been implemented in various applications in previous literature [21,[28][29][30][31][32][33][34][35][36][37].…”

Terminal Synergetic Control for Biological Control of Sugarcane Borer

“…In the TSC method, various dynamic evolutions and/or macro variables, which hold the property of finite time stability, are selected [41,42,47,51,58,61]. Apart from the conventional engineering systems, the different versions of the synergetic control stated above have been employed for biological systems [21,22,27,29,46,47,48]. Specifically, biological pest control strategies have been developed through the SC design shown in previous works [27,29].…”

Design an Optimal Fractional Order PID Controller Based on New Algorithms and a Fuzzy Logic Controller to Regulate Type 1 Diabetes Patients

“…Since the application of fractional calculus is important in control engineering through modeling and control design due to its ability to improve the performance of closed-loop systems and increase robustness, the fractional order controllers are considered a design substitute to classical controllers and one of the main advantages is better system characterization [26,27]. and increased flexibility.…”

“…and increased flexibility. fractional order is important for improving closed-loop performance, and being able to meet more performance specifications as well as increased durability compared to the classical PID controller [26,27]. That is why our contribution to this research was on the application of a FOPID controller for good blood glucose control, closed loop control, and good response determination respectively.…”