Precision coordination and motion control of multiple systems via iterative learning control
Barton, Kira L.
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https://hdl.handle.net/2142/18394
Description
Title
Precision coordination and motion control of multiple systems via iterative learning control
Author(s)
Barton, Kira L.
Issue Date
2011-01-14T22:48:59Z
Director of Research (if dissertation) or Advisor (if thesis)
Alleyne, Andrew G.
Doctoral Committee Chair(s)
Alleyne, Andrew G.
Committee Member(s)
Ferreira, Placid M.
Dullerud, Geir E.
Salapaka, Srinivasa M.
Pao, Lucy
Department of Study
Mechanical Sci & Engineering
Discipline
Mechanical Engineering
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
Ph.D.
Degree Level
Dissertation
Keyword(s)
Iterative Learning Control
Coordination
Precision Motion Control
Manufacturing
Abstract
In today's engineering world, many emerging applications ranging from manufacturing to the autonomous vehicle industry require coordination of multiple systems. Traditional approaches for controlling these systems often neglect the underlying coupling in the application. To stay at the forefront of these fields requires the development of innovative approaches to new challenges. The research in this dissertation focuses on designing novel control strategies for coordinated applications. Electrohydrodynamic jet (E-jet) printing, an example of an emerging micro/nano-manufacturing process with applications in biotechnology and flexible electronics, requires multiple systems to work in a coordinated manner to achieve a desired objective. Repetitive execution of processes such as E-jet can be harnessed to achieve high performance. Iterative learning control (ILC) is an adaptive control technique for improving process performance in systems that execute a task repetitively. This research simultaneously exploits the repetitiveness and inherent coupling of the desired outcome by applying a coordinated ILC approach to processes such as E-jet. The versatility of this approach will be demonstrated through applications ranging from robotics to emerging manufacturing processes.
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