Multivariable Modeling and Control of the Response to Anesthesia
Lin, Hui-Hung
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https://hdl.handle.net/2142/83850
Description
Title
Multivariable Modeling and Control of the Response to Anesthesia
Author(s)
Lin, Hui-Hung
Issue Date
2006
Doctoral Committee Chair(s)
Beck, Carolyn
Department of Study
Mechanical Engineering
Discipline
Mechanical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Health Sciences, Medicine and Surgery
Language
eng
Abstract
To address these shortcomings, this dissertation proposes the use of piecewise-linear multivariable models of the effects of anesthetic and stimuli inputs on patient vital signs. These models are developed by utilizing data-based system identification methods. Different model structures such as linear time invariant (LTI), piecewise linear switching and parameter-varying, are investigated and verified. Robust gain scheduled controllers are constructed and simulated using a linear parameter varying (LPV) framework. The use of multivariable state-space models for patient modeling is novel in this research area, as is the proposed use of piecewise-linear models. The modeling results indicate that the proposed piecewise-linear models yield improved simulation responses over traditional PK-PD models, in comparisons made with respect to single-output effects. Further, individual models may provide reasonable central models in the sense that simulated output responses obtained by applying the input data set for one volunteer to the piecewise-linear models for other volunteers produces an acceptable fit to the output data for the first volunteer. Similar results are found for our constructed individual controllers when applied as a generic controller for other volunteer data.
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