Quantized sampled-data static output feedback control of the glucose–insulin system

FPGA-Based Implementation of a Digital Insulin-Glucose Regulator for Type 2 Diabetic Patients

“…Under the clinical validation framework, the differential equations describing the nonlinear time-delay of the glucose-insulin system employed to design the proposed glucose regulator are the following [17,30,31]:…”

“…In this regard, sampled-data glucose regulators for T2DM patients have been proposed by exploiting both insulin and glucose measurements [14,15]. However, for real time AP operations, direct insulin measurements are not exploitable since they need the use of specific chemical reagents, a drawback that can be only overcome by measuring the blood glucose concentration [16,17]. For this, efforts have been focused on the hardware design and implementation of glucose regulators to achieve control systems for portable and wearable devices operating in low-voltage low-power conditions to ensure reliability, safety, and low cost [18][19][20][21][22].…”

“…In order to avoid this problem, Field Programmable Gate Array (FPGA)-based solutions are largely used for fast prototyping and testing of full-custom integrated solutions and to control the communication of digital systems for biomedical applications [26][27][28][29]. In this sense, in [17] is reported the theoretical model of a digital static output feedback glucose regulator considering the presence of quantization in both the input and output regulator channels. By following the theoretical model discussed in [17], aim of this paper is to present the fully-hardware implementation on an FPGA board of the quantized sampled-data glucose regulator system for T2DM patients.…”

“…In this sense, in [17] is reported the theoretical model of a digital static output feedback glucose regulator considering the presence of quantization in both the input and output regulator channels. By following the theoretical model discussed in [17], aim of this paper is to present the fully-hardware implementation on an FPGA board of the quantized sampled-data glucose regulator system for T2DM patients. With respect to the previous work [29], this paper includes a complete detailed description of the implemented digital architecture and reports a series of measurements to validate the performances of the insulin-glucose regulator applied on a population of one hundred different Virtual Patients (VPs) by employing a comprehensive theoretical model recognized by the U.S. Food and Drug Administration for the pre-clinical validation of the glucose control strategies.…”

Sample-data output-feedback parameter variable control of glucose for type 1 diabetes mellitus patients

“…In the present work, the design of the output-feedback controller is based on the nonlinear Bergman minimal model (BMM). This model provides a suitable swap between nonlinear features of the glucose-insulin system and the model complexity (Di Ferdinando et al, 2021). Different types of control approaches based on linear and nonlinear models have been presented to the glucose-insulin level regulation in the literature, such as conventional proportional–integral–derivative (PID) control schemes (Weinzimer et al, 2008), robust and adaptive control algorithms (Lunze et al, 2013), model predictive controllers (Hovorka et al, 2004), fuzzy logic control (Nath et al, 2016), neural network control (Trajanoski and Wach, 1998), which have been utilized for the BGC regulation of T1DM patients.…”