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Disturbance Modelling for Minimum Variance Control in Adaptive Optics Systems Using Wavefront Sensor Sampled-Data

机译:使用波前传感器采样数据的自适应光学系统中最小方差控制的扰动建模

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摘要

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.
机译:现代大型望远镜是基于自适应光学系统在减轻波前扭曲对天文图像上的不利影响的效力。在天文自适应光学系统中,波前扭曲的主要来源是由风或仪器系统引起的大气湍流和机械振动,例如风扇和冷却泵。通过基于足够和准确的模型的控制定律,通常达到波前扭曲的减轻。在本文中,我们开发了一种基于连续时间阻尼振荡器的建模技术和削弱的似然方法来估计波前传感器时域采样数据的扰动模型的参数。另一方面,当模型不准确时,影响最小方差控制器的性能受到影响。我们表明,我们的建模和识别技术不仅允许更准确的估计,而且还可用于更好的最小方差控制性能。我们通过数值模拟说明了我们提案的好处。

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