AO systems aim at detecting and correcting for optical distortions induced by atmospheric turbulences. They are also extremely sensitive to extraneous sources of perturbation such as vibrations, which degrade the performance. The Gemini South telescope has currently two main AO systems: the Gemini Multi Conjugated AO System GeMS and the Gemini Planet Imager GPI. GeMS is operational and regularly used for science observation delivering close to diffraction limit resolution over a large field of view (85×85 arcsec2). Performance limitation due to the use of an integrator for tip-tilt control is here explored. In particular, this type of controller does not allow for the mitigation of vibrations with an arbitrary natural frequency. We have thus implemented a tip-tilt Linear Quadratic Gaussian (LQG) controller with different underlying perturbation models: (i) a sum of autoregressive models of order 2 identified from an estimated power spectrum density (s-AR2) of the perturbation,1 already tested on CANARY2 and routinely used on SPHERE;3 (ii) cascaded ARMA models of order 2 identified using prediction error minimization (c-PEM) as proposed in.4, 5 Both s-AR2 and c-PEM were parameterized to produce tip or tilt state-space models up to order 20 and 30 respectively. We discuss the parallelized implementation in the real time computer and the expected performance. On-sky tests are scheduled during the November 2016 run or the January 2017 run.
GeMS, the Gemini South MCAO System, has now been in operation for 3 years with the near infrared imager GSAOI. We first review the performance obtained by the system, the science cases and the current operational model. In the very near future, GeMS will undergo a profound metamorphosis, as we will integrate a new NGS wavefront sensor, replace the current 50W laser with a more robust one and prepare for a new operational model where operations will shift from the mountain to the base facility. Along this major evolution, we are also presenting several improvements on the loop control, calibrations and automatization of this complex system. We discuss here the progress of the different upgrades and what we expect in terms of performance improvements and operational efficiency.
Linear Quadratic Gaussian (LQG) control has gained significant ground in astronomical AO. On-line re-tuning of LQG while keeping the AO loop engaged is crucial to match changes in disturbance conditions. However, switching between AO controllers generates control "bumps" which may compromise stability and performance. Control bumps can be eliminated by adjusting the new controllers internal space to ensure maximum continuity of the control trajectory. In this work, we show how to implement this procedure in the case of a tip and tilt control loop using an additional piece of RTC software, the "control switching adapter".
AO optimal control relies centrally on a stochastic model of the turbulence. Models based on both Cn2 spatial priors and temporal dynamics have been used for LQG control for both SCAO and MOAO systems. In this work, we propose turbulence models that account for both wind norm and direction, combining a wind direction-dependent displacement operator with the "boiling turbulence" assumption. We define two extrapolation strategies to complete this new model, and we compare their performance with the LQG control based solely on wind norm priors, through frozen flow simulations. Finally, we discuss about the application of this formalism to WFAO systems.