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Identification of adaptive optics system model with extended data set

Erol, B; Altıner, B; Delibaşı, A; (2024) Identification of adaptive optics system model with extended data set. Journal of the Faculty of Engineering and Architecture of Gazi University , 39 (3) pp. 1825-1836. 10.17341/gazimmfd.1096996. Green open access

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Abstract

Deformable mirrors are the main component of adaptive optics systems and are effective devices for correcting wavefront distortions caused by optical phenomena. For performance analysis and model-based control of adaptive optics systems used in many applications, modelling approaches that reflect the system behavior with high fidelity are needed. System identification techniques, which are an effective approach for this purpose, are prominent in data-driven modelling of complex systems. However, in this approach, the selection of inputs that reflect the system characteristics and meet the target modelling performance is an important problem. The main objective of this study is to determine these inputs. In this study, based on the Hadamard input set developed in the literature for this purpose, an input set extended with Zernike modes used in the modelling of optical distortions is proposed. The success of the extended input set on model fidelity is analyzed within the framework of the mean squared error metric by comparing it with other input sets in the literature on an experimental setup. It is observed that a high-fidelity model between the deformable mirror (DM) and the wavefront sensor (WFS) is produced with the input set used. The success of the proposed technique is tested on adaptive optics test-bench in Hardware-in-the-Loop Simulation (HIL) using a widely used similarity metric.

Type: Article
Title: Identification of adaptive optics system model with extended data set
Open access status: An open access version is available from UCL Discovery
DOI: 10.17341/gazimmfd.1096996
Publisher version: https://doi.org/10.17341/gazimmfd.1096996
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10194921
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