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Advances in Artificial Pancreas Systems

Adaptive and Multivariable Predictive Control

  • Ali Cinar
  • Kamuran Turksoy

Part of the SpringerBriefs in Bioengineering book series (BRIEFSBIOENG)

Table of contents

  1. Front Matter
    Pages i-xii
  2. Ali Cinar, Kamuran Turksoy
    Pages 1-7
  3. Ali Cinar, Kamuran Turksoy
    Pages 9-21
  4. Ali Cinar, Kamuran Turksoy
    Pages 33-50
  5. Ali Cinar, Kamuran Turksoy
    Pages 51-54
  6. Ali Cinar, Kamuran Turksoy
    Pages 55-63
  7. Ali Cinar, Kamuran Turksoy
    Pages 65-82
  8. Ali Cinar, Kamuran Turksoy
    Pages 83-87
  9. Ali Cinar, Kamuran Turksoy
    Pages 89-95
  10. Ali Cinar, Kamuran Turksoy
    Pages 97-99
  11. Ali Cinar, Kamuran Turksoy
    Pages 101-103
  12. Back Matter
    Pages 105-119

About this book

Introduction

This brief introduces recursive modeling techniques that take account of variations in blood glucose concentration within and between individuals. It describes their use in developing multivariable models in early-warning systems for hypo- and hyperglycemia; these models are more accurate than those solely reliant on glucose and insulin concentrations because they can accommodate other relevant influences like physical activity, stress and sleep.

Such factors also contribute to the accuracy of the adaptive control systems present in the artificial pancreas which is the focus of the brief, as their presence is indicated before they have an apparent effect on the glucose concentration and so can be more easily compensated. The adaptive controller is based on generalized predictive control techniques and also includes rules for changing controller parameters or structure based on the values of physiological variables. Simulation studies and clinical studies are reported to illustrate the performance of the techniques presented.

Keywords

Artificial Pancreas Model-based Control Type 1 Diabetes Alternative Control Techniques Hypoglycemia Alarm Hyperglycemia Alarm Multivariable Models Physical Activity Recursive Identification

Authors and affiliations

  • Ali Cinar
    • 1
  • Kamuran Turksoy
    • 2
  1. 1.Department of Biological and Chemical EngineeringIllinois Institute of TechnologyChicagoUSA
  2. 2.Department of Biomedical EngineeringIllinois Institute of TechnologyChicagoUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-319-72245-0
  • Copyright Information The Author(s) 2018
  • Publisher Name Springer, Cham
  • eBook Packages Engineering
  • Print ISBN 978-3-319-72244-3
  • Online ISBN 978-3-319-72245-0
  • Series Print ISSN 2193-097X
  • Series Online ISSN 2193-0988
  • Buy this book on publisher's site