Comparison of predictive control laws in adaptive optics for free-space optical communications

Jonathan Dray; Baptiste Sinquin; Morgan Gray; Benoit Neichel; Cédric Taïssir Héritier; Carlos M. Correia; Raissa Camelo; Jalo Nousiainen; Thierry Fusco; Cyril Petit; Armin Schimpf; Julien Charton

doi:10.1117/12.3019728

27 August 2024 Comparison of predictive control laws in adaptive optics for free-space optical communications

Jonathan Dray, Baptiste Sinquin, Morgan Gray, Benoit Neichel, Cédric Taïssir Héritier, Carlos M. Correia, Raissa Camelo, Jalo Nousiainen, Thierry Fusco, Cyril Petit, Armin Schimpf, Julien Charton

Author Affiliations +

Proceedings Volume 13097, Adaptive Optics Systems IX; 130977W (2024) https://doi.org/10.1117/12.3019728
Event: SPIE Astronomical Telescopes + Instrumentation, 2024, Yokohama, Japan

Conference Poster

Abstract

The reliability of Free Space Optical (FSO) communications between a ground station and celestial objects is significantly hampered by the variability in atmospheric conditions. Enhancing the system’s capabilities to recover the received signal can significantly increase the robustness and broaden the operational scope of this type of communication. One of the most promising avenues for improvement entails integrating Adaptive Optics systems with the latest Machine Learning techniques. We study different control laws based on a classical integrator, a LQG with a Kalman filter (with a second order autoregressive model) and a Reinforcement Learning approach: we evaluate the performance of the three control laws with the Strehl ratio.

Citation Download Citation

Jonathan Dray, Baptiste Sinquin, Morgan Gray, Benoit Neichel, Cédric Taïssir Héritier, Carlos M. Correia, Raissa Camelo, Jalo Nousiainen, Thierry Fusco, Cyril Petit, Armin Schimpf, and Julien Charton "Comparison of predictive control laws in adaptive optics for free-space optical communications", Proc. SPIE 13097, Adaptive Optics Systems IX, 130977W (27 August 2024); https://doi.org/10.1117/12.3019728

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available