Optimization of adaptive optics correction during observations: algorithms and system parameters identification in closed-loop
Optimization of adaptive optics correction during observations: algorithms and system parameters identification in closed-loop
复制标题
观测期间自适应光学校正的优化：闭环中的算法和系统参数识别
DOI：
10.1117/12.926574
复制
发表时间：
2012
影响因子：
4.8
通讯作者：
É. Thiébaut
中科院分区：
文献类型：
--
作者：
C. Béchet;M. Tallon;É. Thiébaut
欧洲超大望远镜上的自适应光学系统（AO），以及2014年超大望远镜上的自适应光学设施等早期探路者，将不再是固定系统。AO不再被孤立在板凳上；有些元件直接位于望远镜的光学序列中，在观测过程中受到环境和约束的影响。为了保证在任何观测时间的良好性能，我们研究了一种自校准策略。我们在这里关注最具挑战性的方面之一：在不引入任何额外干扰的情况下，在闭环观测期间识别系统参数。这种问题在识别理论中是难以解决的。我们最近提出了一种识别方法（bsamchet et al., AO4ELT2 Conference, 2011），并在模拟中获得了有希望的结果。为了巩固这些进展，我们在本文中回到方程并提供理论分析来证明算法的选择。我们强调了使用增量数据和命令去相关干扰的好处。我们还介绍了该方法的两种实现，目前正在欧洲南方天文台进行研究。
The adaptive optics (AO) on the European Extremely Large Telescope, as well as earlier pathfinders like the Adaptive Optics Facility, at the Very Large Telescope in 2014, will no longer be stationary systems. AO is no longer isolated on a bench; some elements are directly in the optical train of the telescope, suffering environment and constrains changes during the observations. To guarantee good performance at any observing time, we investigate a self-calibration strategy. We focus here on one of the most challenging aspects: the identification of system parameters during closed-loop observations without introducing any additional disturbance. Such problem is known in the identification theory to be difficult to solve. We have recently presented (Béchet et al., AO4ELT2 Conference, 2011) an identification method for this, with promising results obtained in simulations. To consolidate these advances, we come back in the present paper to the equations and provide a theoretical analysis to justify the choice of the algorithm. We highlight the benefit of using incremental data and commands to decorrelate the disturbance. We also present 2 implementations of the method, currently studied at the European Southern Observatory.