Data-based modelling of low-order modes for AO control: what do on-sky experiments tell us?

Baptiste Sinquin (1) , Caroline Kulcsár (1) , Léonard Prengère (2, 1) , Henri-François Raynaud (1) , Eric Gendron (3) , James Osborn (4) , Alastair Basden (4) , Jean-Marc Conan (2) , Nazim Bharmal (4) , Lisa Bardou (4) , Lazar Staykov (4) , Tim Morris (4) , Tristan Buey (3) , Fanny Chemla (5) , Matthieu Cohen (5)

1 Laboratoire Charles Fabry / Spim
2 DOTA, ONERA, Université Paris Saclay (COmUE) [Châtillon]
3 LESIA - Laboratoire d'études spatiales et d'instrumentation en astrophysique = Laboratory of Space Studies and Instrumentation in Astrophysics
4 Durham University
5 GEPI - Galaxies, Etoiles, Physique, Instrumentation

It is well-known that data-driven models for the tip-tilt modes significantly improve the performance of Adaptive Optics (AO) systems as it allows to compensate for vibration-induced disturbances. Whether identifying from data the temporal dynamics of more modes makes an impact on the performance has been studied on-sky with the CANARY demonstrator at the William Herschel Telescope in July 2019. In this brief paper, we report on these experiments using both Strehl ratios computed from the science camera in H band or by replaying the AO telemetry data in numerical simulations. We show that Linear Quadratic Gaussian (LQG) controllers that embed a data-driven model for the low-orders (that are not limited to the tip-tilt) improve the performance of the AO for two different dynamical behaviours of the atmospheric turbulence.

Mots clés: adaptive optics; Linear-Quadratic-Gaussian control; Kalman filtering; subspace identification; turbulence modeling; on-sky validation

Domaines: Sciences de l'ingénieur [physics]; Physique [physics]

Baptiste Sinquin, Caroline Kulcsár, Léonard Prengère, Henri-François Raynaud, Eric Gendron, et al.. Data-based modelling of low-order modes for AO control: what do on-sky experiments tell us?. COAT-2019 - workshop (Communications and Observations through Atmospheric Turbulence: characterization and mitigation), ONERA, Dec 2019, Châtillon, France. ⟨10.34693/COAT2019-S3-002⟩. ⟨hal-03146244⟩