Nonlinear Control for Blood Glucose Regulation of Diabetic Patients: An LMI-Based Approach exposes readers to the various existing mathematical models that define the dynamics of glucose-insulin for Type 1 diabetes patients. After providing insights into the mathematical model of patients, the authors discuss the need and emergence of new control techniques that can lead to further development of an artificial pancreas. The book presents various nonlinear control techniques to address the challenges that Type 1 diabetic patients face in maintaining their blood glucose level in the safe range (70-180 mg/dl). The closed-loop solution provided by the artificial pancreas depends mainly on the effectiveness of the control algorithm, which acts as the brain of the system. APS control algorithms require a mathematical model of the gluco-regulatory system of the T1D patients for their design. Since the gluco-regulatory system is inherently nonlinear and largely affected by external disturbances and parametric uncertainty, developing an accurate model is very difficult. Presents control-oriented modeling of the gluco-regulatory system of Type 1 diabetic patients using input-output data Demonstrates the design of a robust insulin delivery mechanism utilizing state estimation information with parametric uncertainties and exogenous disturbance in the framework of Linear Matrix Inequality (LMI) Introduces readers to the relevance and effectiveness of powerful nonlinear controllers for the Artificial Pancreas Provides the first book on LMI-based nonlinear control techniques for the Artificial Pancreas

This book gathers selected research papers presented at the Third International Conference on Communication and Intelligent Systems (ICCIS 2021), organized by National institute of Technology, Delhi, India, during December 18–19, 2021. This book presents a collection of state-of-the-art research work involving cutting-edge technologies for communication and intelligent systems. Over the past few years, advances in artificial intelligence and machine learning have sparked new research efforts around the globe, which explore novel ways of developing intelligent systems and smart communication technologies. The book presents single- and multi-disciplinary research on these themes in order to make the latest results available in a single, readily accessible source.

This book presents closed-loop blood glucose control in a simple manner, which includes the hardware and "software" components that make up the control system. It provides examples on how mathematical models are formulated as well as the control algorithms that stem from mathematical exercises. The book also describes the basic physiology of blood glucose regulation during fasting and meal from a functional level.

This book tackles the problem of overshoot and undershoot in blood glucose levels caused by delay in the effects of carbohydrate consumption and insulin administration. The ideas presented here will be very important in maintaining the welfare of insulin-dependent diabetics and avoiding the damaging effects of unpredicted swings in blood glucose – accurate prediction enables the implementation of counter-measures. The glucose prediction algorithms described are also a key and critical ingredient of automated insulin delivery systems, the so-called “artificial pancreas”. The authors address the topic of blood-glucose prediction from medical, scientific and technological points of view. Simulation studies are utilized for complementary analysis but the primary focus of this book is on real applications, using clinical data from diabetic subjects. The text details the current state of the art by surveying prediction algorithms, and then moves beyond it with the most recent advances in data-based modeling of glucose metabolism. The topic of performance evaluation is discussed and the relationship of clinical and technological needs and goals examined with regard to their implications for medical devices employing prediction algorithms. Practical and theoretical questions associated with such devices and their solutions are highlighted. This book shows researchers interested in biomedical device technology and control researchers working with predictive algorithms how incorporation of predictive algorithms into the next generation of portable glucose measurement can make treatment of diabetes safer and more efficient.

Since delays are present in 99% of industrial processes, Control Strategy for Time-delay Systems covers all the important features of real-world practical applications which will be valuable to practicing engineers and specialists The book presents the views of the editors on promising research directions and future industrial applications in this area. Although the fundamentals of time-delay systems are discussed, the book focuses on the advanced modelling and control of such systems and will provide the analysis and test (or simulation) results of nearly every technique described in the book For this purpose, highly complex models are introduced to ?describe the mentioned new applications which are characterized by ?time-varying delays with intermittent and stochastic nature, several types of nonlinearities, and the presence ?of different time-scales. Researchers, practitioners and PhD students will gain insights into the prevailing trends in design and operation of real-time control systems, reviewing the shortcomings and future developments concerning the practical system issues such as standardization, protection and design.

There has been much advancement in the field of medicine over the course of human history, but especially in the last century. Many medicinal theories have come and gone with more accurate and up-to-date research. Today testing and validation of research is often done with computers and mathematical modeling. One of the common fields in medicine which uses similar computer simulation is insulin replacement therapy for diabetic patients. A diabetic patient lacks the capability of naturally producing insulin the human body needs to regulate blood sugar. The pancreas is responsible for producing insulin to counteract the constant fluctuations in blood sugar. Many factors such as eating, exercising and even sleeping will cause blood sugar levels to rise and fall. Without regular doses of insulin to regulate blood sugar, diabetic patients can experience health complications. Many methods of insulin replacement for diabetic patients have been used throughout the history of treating diabetes. The most innovative and current methods of insulin replacement today stems from the invention of the artificial pancreas. This thesis focuses on the design of a controller for the artificial pancreas with the goal of maximizing its effectiveness. A mathematical metabolic model of the human body, which is validated by the FDA to be used in nonhuman virtual trials, is used. With this model, the user is able to define a wide variety of parameters and most importantly design a controller to make the closed loop system work as effectively as possible. There are many methods that have been used to design a controller, For this thesis, the focus will be evaluating the use of Fuzzy Logic at the heart of the controller for the artificial pancreas. It is shown that with the combination of the mathematical model and the Fuzzy Logic controller, improved performance was achieved. Various implementations of Fuzzy Logic control are detailed and compared to other methods developed by other researchers. The results show Fuzzy Logic has the potential to be a very effective method to use for the control of an artificial pancreas.

Diabetes Without Needles: Non-invasive Diagnostics and Health Management provides a comprehensive and objective compilation of the most promising noninvasive methods for glucose monitoring, including an in-depth analysis of their advantages and disadvantages in terms of biochemical processes. The latest advances in the field are discussed, including methods such as optical measurements, electrochemical measurements, exhaled breath analysis, direct measurements of glucose in the blood using noninvasive techniques, and the indirect analysis of biomarkers that are related to the glycemia. The book's author also presents recommendations for future research directions in this field. This book is a valuable resource for researchers in the areas of diabetes, noninvasive methods and diagnostics development. Appeals to a multidisciplinary audience, including scientists, researchers and clinicians with an interest in noninvasive blood glucose monitoring technologies Features the latest advances in the field of noninvasive methods for diabetes monitoring, including recent results, perspectives and challenges Covers various noninvasive methods, including optical measurements, electrochemical, exhaled breath analysis, and more