Subspace identification of low-dimensional Structural-Thermal-Optical-Performance (STOP) models of reflective optics. (arXiv:2208.02333v1 [astro-ph.IM])
<a href="http://arxiv.org/find/astro-ph/1/au:+Haber_A/0/1/0/all/0/1">Aleksandar Haber</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Draganov_J/0/1/0/all/0/1">John E. Draganov</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Krainak_M/0/1/0/all/0/1">Michael Krainak</a>
In this paper, we investigate the feasibility of using subspace system
identification techniques for estimating transient Structural-Thermal-Optical
Performance (STOP) models of reflective optics. As a test case, we use a
Newtonian telescope structure. This work is motivated by the need for the
development of model-based data-driven techniques for prediction, estimation,
and control of thermal effects and thermally-induced wavefront aberrations in
optical systems, such as ground and space telescopes, optical instruments
operating in harsh environments, optical lithography machines, and optical
components of high-power laser systems. We estimate and validate a state-space
model of a transient STOP dynamics. First, we model the system in COMSOL
Multiphysics. Then, we use LiveLink for MATLAB software module to export the
wavefront aberrations data from COMSOL to MATLAB. This data is used to test the
subspace identification method that is implemented in Python. One of the main
challenges in modeling and estimation of STOP models is that they are
inherently large-dimensional. The large-scale nature of STOP models originates
from the coupling of optical, thermal, and structural phenomena and physical
processes. Our results show that large-dimensional STOP dynamics of the
considered optical system can be accurately estimated by low-dimensional
state-space models. Due to their low-dimensional nature and state-space forms,
these models can effectively be used for the prediction, estimation, and
control of thermally-induced wavefront aberrations. The developed MATLAB,
COMSOL, and Python codes are available online.
In this paper, we investigate the feasibility of using subspace system
identification techniques for estimating transient Structural-Thermal-Optical
Performance (STOP) models of reflective optics. As a test case, we use a
Newtonian telescope structure. This work is motivated by the need for the
development of model-based data-driven techniques for prediction, estimation,
and control of thermal effects and thermally-induced wavefront aberrations in
optical systems, such as ground and space telescopes, optical instruments
operating in harsh environments, optical lithography machines, and optical
components of high-power laser systems. We estimate and validate a state-space
model of a transient STOP dynamics. First, we model the system in COMSOL
Multiphysics. Then, we use LiveLink for MATLAB software module to export the
wavefront aberrations data from COMSOL to MATLAB. This data is used to test the
subspace identification method that is implemented in Python. One of the main
challenges in modeling and estimation of STOP models is that they are
inherently large-dimensional. The large-scale nature of STOP models originates
from the coupling of optical, thermal, and structural phenomena and physical
processes. Our results show that large-dimensional STOP dynamics of the
considered optical system can be accurately estimated by low-dimensional
state-space models. Due to their low-dimensional nature and state-space forms,
these models can effectively be used for the prediction, estimation, and
control of thermally-induced wavefront aberrations. The developed MATLAB,
COMSOL, and Python codes are available online.
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