Orientation of an Optically Trapped Non-Spherical Micro-Particle using Iterative Learning Control

Connor Edlund, Rachit Shrivastava, Murti V. Salapaka

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

1 Scopus citations


Optical trapping of micron to sub-micron sized particles has enabled significant advancements in science and engineering. For spherical particles, the use of dynamic model-based feedback control has resulted in increasingly fine control over particle position and in turn new scientific discoveries. Extending the success of dynamic control to the case of particles of arbitrary shape is difficult as the complex interactions between the particle and laser light do not lend themselves well to dynamic models suitable for real-time use. In this article a learning-based, model-free control approach for the automated manipulation of non-spherical particles is introduced. This approach is instantiated with the automatic out-of-plane rotation of a sub-micron cylinder in dynamic simulation using visual position and orientation feedback.

Original languageEnglish (US)
Title of host publication2022 American Control Conference, ACC 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Electronic)9781665451963
StatePublished - 2022
Event2022 American Control Conference, ACC 2022 - Atlanta, United States
Duration: Jun 8 2022Jun 10 2022

Publication series

Name2022 American Control Conference (ACC)


Conference2022 American Control Conference, ACC 2022
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© 2022 American Automatic Control Council.


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