Optimal time-varying ILC design to monotonically minimize converged error

Marina Tharayil, Andrew Alleyne

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper presents a design method for Iterative Learning Control (ILC) algorithms using time-varying Q-filters. The design of an optimal bandwidth profile for a given plant model is formulated as a constrained minimization problem. The resultant time-varying ILC algorithm generates the lowest converged error norm possible while guaranteeing monotonic convergence. The time-varying ILC background, problem setup to optimize the time-varying Q-filter bandwidth, as well as results obtained using computational methods are presented. A simulation example is used to demonstrate the potential benefits of the algorithm in comparison with LTI ILC. Lastly, experimental validation is provided by application of the ILC algorithm developed here on a Microscale Robotic Deposition system for precision motion control.

Original languageEnglish (US)
Title of host publicationProceedings of the ASME Dynamic Systems and Control Division 2005
Pages3-10
Number of pages8
Edition1 PART A
DOIs
StatePublished - 2005
Event2005 ASME International Mechanical Engineering Congress and Exposition, IMECE 2005 - Orlando, FL, United States
Duration: Nov 5 2005Nov 11 2005

Publication series

NameAmerican Society of Mechanical Engineers, Dynamic Systems and Control Division (Publication) DSC
Number1 PART A
Volume74 DSC

Other

Other2005 ASME International Mechanical Engineering Congress and Exposition, IMECE 2005
Country/TerritoryUnited States
CityOrlando, FL
Period11/5/0511/11/05

ASJC Scopus subject areas

  • Mechanical Engineering
  • Software

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