Chaotic genetic algorithm for wavefront correction in adaptive optics

  • Stephen Kotiang*
  • , Jae Ho Choi
  • *Corresponding author for this work

Research output: Contribution to conferenceConference paperpeer-review

Abstract

Chaotic genetic algorithm (CGA) is presented as an optimization algorithm for sensorless adaptive optics system to compensate atmospheric wave aberration. Chaos search strategy is incorporated into standard genetic algorithm by the logistic function that possess convergent, bifurcating, and chaotic characteristics during evolution to control the convergence of genetic algorithm. A real number encoding method is adopted in the search process and CGA is used to control a 61-actuator deformable membrane mirror (DM).The algorithm uses light intensity detected on the focal plane as the objective function to optimize, and the simulation results show CGAperforms faster than GA and thus can effectively be used in AO systems.

Original languageEnglish
Title of host publicationElectronics, Mechatronics and Automation III
EditorsMaode Ma, Amanda F. Wu, Z. Afrasiabi, Z. Afrasiabi, Maode Ma, Amanda F. Wu
PublisherTrans Tech Publications Ltd
Pages293-297
Number of pages5
ISBN (Electronic)9783038352976, 9783038352976
DOIs
StatePublished - 2014
Event3rd International Conference on Electronics, Mechatronics and Automation, ICEMA 2014 - Dubai, United Arab Emirates
Duration: 2014.08.222014.08.23

Publication series

NameApplied Mechanics and Materials
Volume666
ISSN (Print)1660-9336
ISSN (Electronic)1662-7482

Conference

Conference3rd International Conference on Electronics, Mechatronics and Automation, ICEMA 2014
Country/TerritoryUnited Arab Emirates
CityDubai
Period14.08.2214.08.23

Keywords

  • Adaptive optics
  • Chaos theory
  • Deformable mirror
  • Genetic algorithm
  • Zernike polynomial

Quacquarelli Symonds(QS) Subject Topics

  • Engineering & Technology

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