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
OriginalsprogEngelsk
BogserieIFAC-PapersOnLine
Vol/bind56
Udgave nummer2
Sider (fra-til)6012-6017
Antal sider6
ISSN1474-6670
DOI
StatusUdgivet - 1 jul. 2023
Begivenhed22nd IFAC World Congress 2023 - Yokohama, Japan
Varighed: 9 jul. 202314 jul. 2023
https://www.ifac2023.org/

Konference

Konference22nd IFAC World Congress 2023
Land/OmrådeJapan
ByYokohama
Periode09/07/202314/07/2023
Internetadresse

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