Model predictive control-based adaptive optics system with deep-learning Shack-Hartmann wavefront sensor

Wei Shiuan Huang, Chia Wei Hsu, Feng Chun Hsu, Chun Yu Lin, Shean Jen Chen*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Model predictive control (MPC) can use the state of the current measurement processing to predict future events and be able to take control processing accordingly. To implement MPC in our adaptive optics system (AOS), a multichannel state-space model is first identified between the driving voltage for a 61-channel deformable mirror (DM) as the input and the 8-order Zernike polynomial coefficients via a lab-made Shack-Hartmann wavefront sensor (SHWS) as the output. Conventionally, the center of weight algorithm is utilized to reconstruct the wavefront from SHWS, but it takes a lot of computation time. Therefore, a deep learning (DL) approach based on U-Net is adopted to rapid reconstruct the wavefront. The U-Net significantly reduces the time to compute the wavefront and also gets the higher accuracy. After that, the MPC controller based on the identified system model is implemented in AOS. Currently, the simulation results demonstrate that the MPC with the DL-SHWS can fast correct the wavefront aberration. Eventually, the MPC-based AOS will be implemented under Robot Operating System (ROS) to achieve real-time control.

Original languageEnglish
Title of host publicationDigital Optical Technologies 2023
EditorsBernard C. Kress, Jurgen W. Czarske
PublisherSPIE
ISBN (Electronic)9781510664579
DOIs
StatePublished - 2023
EventDigital Optical Technologies 2023 - Munich, Germany
Duration: 26 Jun 202328 Jun 2023

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume12624
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

ConferenceDigital Optical Technologies 2023
Country/TerritoryGermany
CityMunich
Period26/06/2328/06/23

Keywords

  • Adaptive optics
  • deep learning
  • model predictive control
  • Shack-Hartmann wavefront sensor
  • system identification

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