Iterative Learning Control for image based visual servoing applications

Erick Sutanto, Andrew G. Alleyne

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

2 Scopus citations


Fabrication of nano/micro-scale functional devices, in the context of a continuous or semi-continuous manufacturing process, is often performed via successive processes in multiple localized zones. As the substrate traverses downstream in the process flow, proper registration of the pre-existing features is necessary prior to entering the next fabrication zone in order to accurately complement previous manufacturing steps. In this work, we consider a 2D planar arrangement where the substrate can be panned and oriented and we performed a direct visual servoing technique to correct both the pose and the translational alignment of a pre-existing feature. Based on the recorded image data, Iterative Learning Control (ILC) is implemented on top of the feedback controller to simultaneously improve the position and orientation tracking precision of the feature.

Original languageEnglish (US)
Title of host publication2014 American Control Conference, ACC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Print)9781479932726
StatePublished - 2014
Externally publishedYes
Event2014 American Control Conference, ACC 2014 - Portland, OR, United States
Duration: Jun 4 2014Jun 6 2014

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619


Other2014 American Control Conference, ACC 2014
Country/TerritoryUnited States
CityPortland, OR


  • Iterative learning control
  • Manufacturing systems
  • Vision-based control


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