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Iterative learning control of a membrane deformable mirror for optimal wavefront correction

机译:膜变形镜的迭代学习控制,可实现最佳波前校正

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摘要

We present an iterative learning control (ILC) algorithm for controlling the shape of a membrane deformable mirror (DM). We furthermore give a physical interpretation of the design parameters of the ILC algorithm. On the basis of this insight, we derive a simple tuning procedure for the ILC algorithm that, in practice, guarantees stable and fast convergence of the membrane to the desired shape. In order to demonstrate the performance of the algorithm, we have built an experimental setup that consists of a commercial membrane DM, a wavefront sensor, and a real-time controller. The experimental results show that, by using the ILC algorithm, we are able to achieve a relatively small error between the real and desired shape of the DM while at the same time we are able to control the saturation of the actuators. Moreover, we show that the ILC algorithm outperforms other control algorithms available in the literature.
机译:我们提出了一种迭代学习控制(ILC)算法,用于控制膜可变形镜(DM)的形状。我们进一步给出了ILC算法设计参数的物理解释。基于此见解,我们为ILC算法推导了一个简单的调整过程,该过程在实践中可确保将膜稳定快速地收敛到所需形状。为了演示该算法的性能,我们建立了一个实验装置,该装置由商用膜DM,波前传感器和实时控制器组成。实验结果表明,通过使用ILC算法,我们能够在DM的实际形状和所需形状之间实现相对较小的误差,同时我们能够控制执行器的饱和度。此外,我们证明了ILC算法的性能优于文献中提供的其他控制算法。

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