Identification, state estimation, and adaptive control of type 'I' diabetic patients

2012 2012

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Abstract (summary)

During the past few decades, biomedical modeling techniques have been applied to improve performance of a wide variety of medical systems that require monitoring and control. Diabetes is one of the most important medical problems. Most of the existing techniques assume the system to be time-invariant, and the original minimal model was modified by deleting some important parameters. In this research, the original minimal model that consists of three differential equations is used. A new differential equation represents a first order infusion pump is added to the set of the differential equations of the minimal model. The Nonlinear Least Squares Method with Levenberg-Marquardt Algorithm is used to estimate the unknown parameters of the differential equations. A new regime-switching control scheme using Proportional-Integral-Derivative (PID) controllers is designed to ensure that the control specifications are met. By comparing different switching schemes, we show that switched PID controllers can improve performance, but frequent switching of controllers is unnecessary. These findings lead to a control strategy that utilizes only a small number of PID controllers in this scheduled adaptation strategy. The regime-switching scheme proves that adaptive control can potentially improve system performance. But it increases control complexity and may create further stability issues. This research investigates patient models and presents a simplified control scheme using observer-based state feedback controller that is able to enhance the performance of the system and meet the design specifications. By comparing different control schemes, it shows that a properly designed observer-based state feedback controller can eliminate the adaptation strategy that PID regime-switching control scheme needs to improve the control performance. Also, the observer-based state feedback control scheme reduces the complexity of the control circuit by eliminating the adaptive control switching components and reduces the cost to build up the circuits.

Indexing (details)

Biomedical engineering;
Electrical engineering
0541: Biomedical engineering
0544: Electrical engineering
Identifier / keyword
Applied sciences; Adaptation; Biomedical modeling; Diabetes; Feedback controller; Insulin control
Identification, state estimation, and adaptive control of type 'I' diabetic patients
Hariri, Ali Mohamad
Number of pages
Publication year
Degree date
School code
DAI-B 73/06, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
Wang, Le Yi
Committee member
Singh, Harpreet; Siy, Pepe; Yaprak, Ece
Wayne State University
Electrical Engineering
University location
United States -- Michigan
Source type
Dissertations & Theses
Document type
Dissertation/thesis number
ProQuest document ID
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
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