Adaptive multi-surrogate model for complex opto-mechanical system alignment

Abstract

Owing to the inherent nonlinearity of surrogate models, they have been widely used in the alignment of complex opto-mechanical systems. Finding the most suitable surrogate model for misalignment wavefront errors is challenging. This study proposes an adaptive multi-surrogate model (AMSM) based on the concept of layer-by-layer approximation and adaptive selection and a compensation mechanism to facilitate the combination of the AMSM and non-dominated sorting genetic algorithm II (NSGA-II). For example, alignment simulations of an off-axis three-mirror anastigmatic (TMA) telescope and a catadioptric microscope objective were performed. The results show that the AMSM is well done in terms of approximate accuracy and efficiency. The application of the proposed method in the off-axis TMA telescope leads to 65.2% and 18.7% reductions in the full-field average RMS wavefront error compared with the traditional sensitivity table method (STM) and radial basis function (RBF) network surrogate model, respectively. Similarly, for the catadioptric microscope objective, there is a reduction of 43.5% and 22.4%, respectively. The AMSM will further promote the development of a surrogate model to align more complex and precise opto-mechanical systems.