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Published by Academic Press 2022-06-15, 2022
ISBN 10: 0323907768 ISBN 13: 9780323907767
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Published by Elsevier Science & Technology, 2022
ISBN 10: 0323907768 ISBN 13: 9780323907767
Language: English
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Published by Elsevier Science & Technology, 2022
ISBN 10: 0323907768 ISBN 13: 9780323907767
Language: English
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ISBN 10: 0323907768 ISBN 13: 9780323907767
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Add to basketTaschenbuch. Condition: Neu. Neuware - 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.
Published by Elsevier Science & Technology, 2022
ISBN 10: 0323907768 ISBN 13: 9780323907767
Language: English
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Add to basketCondition: New. InhaltsverzeichnisSection 1: Introduction1. The History, Present & Future progression of Artificial Pancreas2. Biomedical Control & its importance in Artificial Pancreas3. A brief discussion in Nonlinear Control Tools.
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Published by Elsevier Science and Technology, GB, 2022
ISBN 10: 0323907768 ISBN 13: 9780323907767
Language: English
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Paperback. Condition: New. 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.
Published by Elsevier Science & Technology, 2022
ISBN 10: 0323907768 ISBN 13: 9780323907767
Language: English
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Published by Elsevier Science and Technology, GB, 2022
ISBN 10: 0323907768 ISBN 13: 9780323907767
Language: English
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Paperback. Condition: New. 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.