Nonlinear Control for Blood Glucose Regulation of Diabetic Patients: An LMI Approach

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 INDICE: Section 1: Introduction1. The History, Present & Future progression of Artificial Pancreas2. Biomedical Control & its importance in Artificial Pancreas3. A brief discussion in Nonlinear Control ToolsSection 2: Type 1 Diabetes: Control Oriented Modelling4. A review on the existing Artificial pancreas Models5. Developing and validating Nonlinear Models based on Input-Output dataSection 3: State Estimation via Robust Nonlinear Observers6. Mathematical formulation of Robust Nonlinear Observers7. State EstimationSection 4: Design of Robust Nonlinear Control Techniques8. Design of Nonlinear Control Technique based on Feedback Linearization9. Design of Robust LMI based Control Techniques10. ConclusionsSection 5: Proposed Architecture for In-Silico Artificial Pancreas11. Sensors and Actuators12. Integrated (in-silico) Model of Artificial Pancreas

• ISBN: 978-0-323-90776-7
• Editorial: Academic Press
• Encuadernacion: Rústica
• Páginas: 232
• Fecha Publicación: 19/08/2022
• Nº Volúmenes: 1
• Idioma: Inglés