Momentum-Based Learning of Nash Equilibria for LISA Pointing Acquisition

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Abstract

This paper addresses the pointing acquisition phase of the Laser Interferometer Space Antenna (LISA) mission as a guidance problem. It is formulated in a cooperative game setup, which solution is a sequence of corrections that can be used as a tracking reference to align all the spacecraft' laser beams simultaneously within the tolerances required for gravitational wave detection. We propose a model-free learning algorithm based on residual-feedback and momentum, for accelerated convergence to stable solutions, i.e. Nash Equilibria. Each spacecraft has 4 degrees of freedom, and the only measured output considered are laser misalignments with the local interferometer sensors. Simulation results demonstrate that the proposed strategy manages to achieve absolute misalignment errors
Original languageEnglish
Book seriesIFAC-PapersOnLine
Volume56
Issue number2
Pages (from-to)6012-6017
Number of pages6
ISSN1474-6670
DOIs
Publication statusPublished - 1 Jul 2023
Event22nd IFAC World Congress 2023 - Yokohama, Japan
Duration: 9 Jul 202314 Jul 2023
https://www.ifac2023.org/

Conference

Conference22nd IFAC World Congress 2023
Country/TerritoryJapan
CityYokohama
Period09/07/202314/07/2023
Internet address

Keywords

  • Decision making and autonomy
  • Extremum seeking and model free adaptive control
  • Game theory
  • High accuracy pointing
  • LISA
  • Satellite constellation
  • Space exploration

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