Abstract
Modern large telescopes are built based on the effectiveness of adaptive optics systems in mitigating the detrimental effects of wavefront distortions on astronomical images. In astronomical adaptive optics systems, the main sources of wavefront distortions are atmospheric turbulence and mechanical vibrations that are induced by the wind or the instrumentation systems, such as fans and cooling pumps. The mitigation of wavefront distortions is typically attained via a control law that is based on an adequate and accurate model. In this paper, we develop a modelling technique based on continuous-time damped-oscillators and on the Whittle’s likelihood method to estimate the parameters of disturbance models from wavefront sensor time-domain sampled-data. On the other hand, when the model is not accurate, the performance of the minimum variance controller is affected. We show that our modelling and identification techniques not only allow for more accurate estimates, but also for better minimum variance control performance. We illustrate the benefits of our proposal via numerical simulations.
Highlights
The last decades have marked the advent of the extremely large telescopes epoch in ground-based astronomy, in which astronomical observatories have experienced a growth in the aperture of their telescopes, see e.g., [1]
This mitigation is achieved by deforming a deformable mirror (DM) in order to compensate the optical aberrations that are measured by a wavefront sensor (WFS), which, in turn, implies the need for both an accurate model of the complete Adaptive optics (AO) system and adequate controllers
We focus on obtaining accurate disturbance models for the design of a minimum variance controller (MVC) in AO systems to improve the performance of the AO system
Summary
The last decades have marked the advent of the extremely large telescopes epoch in ground-based astronomy, in which astronomical observatories have experienced a growth in the aperture of their telescopes, see e.g., [1]. In order to improve the quality of ground astronomical images, it is essential to obtain accurate models that define the dynamics of the plant that is comprised of the cascade connection of the DM and the WFS [11,12,13] and the accurate model parameters of all sources of noise and disturbances (turbulence and vibrations) that allow for implementing effective control techniques. The MVC control performance improves in about 19% when the controller is designed using the model that was obtained from our proposed identification technique.
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