Abstract/Details

Advancing adaptive model predictive control for biological applications


2011 2011

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Abstract (summary)

The fundamental principles employed to rationally direct biological processes have evolved primarily based on results from trial-and-error experiments guided by scientific intuition. However, the inherent complexity of the intracellular signaling events that drive these processes hinders the ability of intuition to efficiently design experiments for obtaining the desired response. There is a critical need to rationalize the design of experiments using quantitative, model-based approaches. The work presented herein aims to address this need by establishing a control-theoretic approach, utilizing both theoretical and experimental components, to facilitate the design of experimental strategies to predictably direct biological processes. Adaptive model predictive control strategies are paired with nonlinear and sparse grid-based optimization approaches to address applications ranging from the control of cellular differentiation to the scheduled dosing of pharmaceuticals. The developed control algorithms were designed to account for the highly uncertain models and practical experimental limitations characteristic to biological systems. However, despite the biological context, these algorithms address challenges which exist for the control any uncertain system and are expected to be broadly applicable.

Indexing (details)


Subject
Biomedical engineering;
Electrical engineering
Classification
0541: Biomedical engineering
0544: Electrical engineering
Identifier / keyword
Applied sciences; Adaptive control; Biological systems; Cellular systems; Multi-scenario control; Sparse grids
Title
Advancing adaptive model predictive control for biological applications
Author
Noble, Sarah Lynn
Number of pages
260
Publication year
2011
Degree date
2011
School code
0183
Source
DAI-B 73/01, Dissertation Abstracts International
Place of publication
Ann Arbor
Country of publication
United States
ISBN
9781124945408
Advisor
Rundell, Ann E.; Balakrishnan, Venkataramanan
Committee member
Hu, Jianghai; Talavage, Thomas M.
University/institution
Purdue University
Department
Electrical and Computer Engineering
University location
United States -- Indiana
Degree
Ph.D.
Source type
Dissertations & Theses
Language
English
Document type
Dissertation/Thesis
Dissertation/thesis number
3477718
ProQuest document ID
901126713
Copyright
Database copyright ProQuest LLC; ProQuest does not claim copyright in the individual underlying works.
Document URL
http://search.proquest.com/docview/901126713
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