Linear controller error budget assessment for classical adaptive optics systems

Juvénal, Rémy; Kulcsár, Caroline; Raynaud, Henri-François; Conan, Jean-Marc

doi:10.1364/josaa.35.001465

Cited by 4 publications

(4 citation statements)

References 28 publications

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“…The relative improvement between both is better preserved for large r 0 (−32 per cent versus −31 per cent) but stays close even for small r 0 (−34 per cent versus −39 per cent). Note that the smaller r 0 , the larger the temporal and aliasing errors, the latter being especially reduced with an LQG controller (Juvénal et al 2018). Results in Table 1 show that the procedure is valid for control performance comparison.…”

Section: Integratormentioning

confidence: 87%

“…To further understand the performance of the proposed controllers and the potential to improve over these solutions, we now detail an error budget based on formulas in Juvénal et al (2018), using simulated disturbance sequences.…”

Section: E R Ro R B U D G E Tmentioning

confidence: 99%

“…The term σ 2 rej quantifies how much the system rejects the turbulent wavefront and can be broken down into three terms: the temporal error σ 2 temp , the aliasing error σ 2 alias due to the WFS finite sampling, and the fitting error σ 2 fit (which is independent of the controller). As in Juvénal et al (2018), we introduce the projectors on the subspaces Im(N) and Im(N) ⊥ ,…”

Section: E R Ro R B U D G E Tmentioning

confidence: 99%

See 2 more Smart Citations

On-sky results for adaptive optics control with data-driven models on low-order modes

Sinquin

Prengère

Kulcsár

et al. 2020

Monthly Notices of the Royal Astronomical Society

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Dedicated tip-tilt loops are commonly implemented on adaptive optics (AO) systems. In addition, a number of recent high-performance systems feature tip-tilt controllers which are more efficient than the integral action controller. In this context, Linear Quadratic Gaussian (LQG) tip-tilt regulators based on stochastic models identified from AO telemetry have demonstrated their capacity to effectively compensate for the cumulated effects of atmospheric disturbance, windshake and vibrations. These tip-tilt LQG regulators can also be periodically re-tuned during AO operations, thus allowing to track changes in the disturbances’ temporal dynamics. This paper investigates the potential benefit of extending the number of low-order modes to be controlled using models identified from AO telemetry. The global stochastic dynamical model of a chosen number of turbulent low-order modes is identified through data-driven modelling from wavefront sensor measurements. The remaining higher modes are modelled using priors with autoregressive models of order 2. The loop is then globally controlled using the optimal LQG regulator build from all these models. Our control strategy allows for combining a dedicated tip-tilt loop with a deformable mirror that corrects for the remaining low-order modes and for the higher orders altogether, without resorting to mode decoupling. Performance results are obtained through evaluation of the Strehl ratio computed on H-band images from the scientific camera, or in replay mode using on-sky AO telemetry recorded in July 2019 on the CANARY instrument.

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Section: Integratormentioning

confidence: 87%

Section: E R Ro R B U D G E Tmentioning

confidence: 99%

Section: E R Ro R B U D G E Tmentioning

confidence: 99%

See 1 more Smart Citation

On-sky results for adaptive optics control with data-driven models on low-order modes

Sinquin

Prengère

Kulcsár

et al. 2020

Monthly Notices of the Royal Astronomical Society

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“…Once the frequency responses of the rejection transfer function (RTF) and noise propagation transfer function have been calculated, the effects on any incoming second-order stationary stochastic process with known power spectral density can be evaluated, allowing in particular to predict the expected value of the residual phase variance -see, Ref. 44 for the general case of linear controllers. These calculations rely on the hypothesis that the AO system is linear and time-invariant, so that to a given input frequency corresponds an output at the same frequency, albeit with possibly a different amplitude and nonzero phase shift.…”

Section: Modal Control Analysismentioning

confidence: 99%

Cascade adaptive optics: contrast performance analysis of a two-stage controller by numerical simulations

Cerpa-Urra¹,

Kasper²,

Kulcsár³

et al. 2022

Preprint

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The contrast performance of current eXtreme Adaptive Optics (XAO) systems can be improved by adding a second AO correction stage featuring its own wavefront sensor, deformable mirror and real-time controller. We develop a dynamical model for such a cascade AO (CAO) system with two stages each controlled by a standard integrator, and study its control properties. We study how such a configuration can improve an existing system without modifying the first stage. We analyze the CAO architecture in general and show how part of the disturbance is transferred from low to high temporal frequencies with a nefarious effect of the 2 nd stage integrator overshoot, and suggest possible ways to mitigate this. We also carry out numerical simulations of the particular case of a 1 st stage AO using a Shack-Hartmann wavefront sensor and a 2 nd stage AO with a smaller deformable mirror running at a higher framerate to reduce temporal error. In this case, we demonstrate that the 2 nd stage improves imaging contrast by one order of magnitude and shortens the decorrelation time of atmospheric turbulence speckles by even a greater factor. The results show that CAO presents a promising and relatively simple way to upgrade some existing XAO systems and achieve improved imaging contrasts fostering a large number of science case including the direct imaging of Exoplanets.

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First on-sky tests of LQG control for a 10m-class telescope: prelude on the Gran Telescopio Canarias adaptive optics system

Marquis,

Raynaud,

Galland

et al. 2024

Adaptive Optics Systems IX

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The Gran Telescopio Canarias (GTC) is being equipped with an Adaptive Optics (AO) system, 1 developed by the Instituto de Astrofísica de Canarias (IAC). 2 The Institut d'Optique Graduate School-Laboratoire Charles Fabry (IOGS-LCF), through a collaboration with the IAC, integrated some high performance control solutions. 3 In this proceeding, we present the first and promising on-sky results on a 10-meter class telescope for such a controller, namely a full Linear Quadratic Gaussian regulator (LQG). We start with a brief description of the GTCAO system, including the data-driven LQG regulator construction. Performance results are then presented with a full LQG regulator in line with the previous on-bench experiments, 3 implemented in DARC, 4 the GTCAO RTC. A comparison is performed with the integrator, the baseline controller, through the comparison of point spread functions acquired on the scientific camera and residual slopes recorded by the wavefront sensor.

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Linear controller error budget assessment for classical adaptive optics systems

Cited by 4 publications

References 28 publications

On-sky results for adaptive optics control with data-driven models on low-order modes

On-sky results for adaptive optics control with data-driven models on low-order modes

Cascade adaptive optics: contrast performance analysis of a two-stage controller by numerical simulations

First on-sky tests of LQG control for a 10m-class telescope: prelude on the Gran Telescopio Canarias adaptive optics system

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