Blood glucose regulation system using model predictive controller

2017 ◽  
Author(s):  
M. Nalini ◽  
V. Balaji ◽  
Vinitha Kumar ◽  
R. Priya ◽  
A. Ulaganayaki ◽  
...  
Keyword(s):  
Blood Glucose ◽  
Glucose Regulation ◽  
Regulation System ◽  
Model Predictive Controller ◽  
Blood Glucose Regulation ◽  
Predictive Controller

scholarly journals Exponential tracking of general references and rejection of general disturbances for nonlinear control systems with applications to the blood glucose regulation system

2021 ◽  
Author(s):  
Weijiu Liu
Keyword(s):  
Control System ◽  
Blood Glucose ◽  
Nonlinear Control ◽  
Glucose Regulation ◽  
Regulation System ◽  
Dimensional System ◽  
General Reference ◽  
Blood Glucose Regulation ◽  
Exponentially Stable ◽  
Pure Imaginary Eigenvalues

In solving the problem of exponential tracking and disturbance rejection, it has been long always assumed that the reference to be tracked and the disturbance to be rejected are generated by an exosystem such as a finite dimensional system with pure imaginary eigenvalues. The aim of this note is to show that this assumption can be removed. For any nonlinear control system subject to a general disturbance, it can be split into a linear exponentially-stable system and a dynamical regulator system. If the dynamical regulator system has a solution, then there exists a feedback and feedforward controller such that an output of the control system exponentially tracks a desired general reference. The result is applied to the blood glucose regulation system.

Blood Glucose Regulation for Diabetic Mellitus Using a Hybrid Intelligent Techniques

2005 ◽  
Author(s):  
Vidya Nandikolla ◽  
Desineni Naidu
Keyword(s):  
Optimal Control ◽  
Blood Glucose ◽  
Control Strategy ◽  
Closed Loop ◽  
Glucose Regulation ◽  
Regulation System ◽  
Blood Glucose Regulation ◽  
Control Scheme ◽  
Optimal Control Scheme ◽  
Soft Control

In this paper, we use a mathematical model for the interaction between the blood glucose and insulin concentration and investigates the on-line control schemes necessary to accomplish an external blood glucose regulation. The dynamic model is described in terms of blood glucose level, and net insulin level in blood as two state variables and external rate of blood glucose concentration as control variable. Using optimal regulation results, an objective is chosen to minimize the deviation of blood glucose from a preset level. The closed-loop optimal control scheme is developed for the biosystem in which a blood glucose sensor feeds information to a pump to release computed amount of insulin into the circulation system. The performance of the proposed optimal control scheme is compared with experimental results. Further to improve the closed-loop optimal performance, a soft control strategy based on adaptive neuro-fuzzy inference system (ANFIS) is devised leading to synergy of hard (optimal) and soft (artificial intelligent) control. ANFIS is a simple learning technique which is implemented in the framework of adaptive neural networks that provides the best optimization tool to find parameters that best fits the data. The application of this synergetic (hard and soft) control strategy to the diabetic regulation system shows good agreement between the experimental data and the theoretical/simulated results.

COEXISTENCE OF THREE OSCILLATORY MODES OF INSULIN SECRETION: MATHEMATICAL MODELING AND RELEVANCE TO GLUCOSE REGULATION

2017 ◽  
Vol 25 (02) ◽  
pp. 341-368
Author(s):  
HYUK KANG ◽  
KYUNGREEM HAN ◽  
SEGUN GOH ◽  
MOOYOUNG CHOI
Keyword(s):  
Mathematical Modeling ◽  
Insulin Secretion ◽  
Blood Glucose ◽  
Numerical Simulations ◽  
Quantitative Information ◽  
Whole Body ◽  
Glucose Regulation ◽  
Regulation System ◽  
Blood Glucose Regulation ◽  
Regulatory Strategies

Insulin secretion in pancreatic [Formula: see text]-cells exhibits three oscillatory modes with distinct period ranges, called fast, slow, and ultradian modes. To unveil the mechanism underlying such oscillatory behaviors and their roles in blood glucose regulation, we propose a combined model for the glucose–insulin regulation system, incorporating both the cell-level insulin secretion mechanism and inter-organ interactions in the blood glucose regulation. Special emphasis is placed on the identification of the mechanism of the slow oscillation and its role associated with the whole-body glucose regulation. Via extensive numerical simulations, we obtain macroscopic behaviors of the three types of insulin/glucose oscillations in the whole-body as well as microscopic behaviors of the membrane potential and the calcium concentration in the [Formula: see text]-cell. Finally, optimal regulatory strategies for the blood glucose level are discussed on the basis of the quantitative information obtained from the mathematical modeling and numerical simulations.

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