Philip L. Neureuther, Kevin Schmidt, T. Bertram, O. Sawodny
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Control oriented modelling and modal analysis of the deformable mirror M4 of the extremely large telescope
ABSTRACT In this article, we derive a mechanical distributed parameter model for the annular sector plate segments of the Extremely Large Telescope’s deformable mirror M4. Additionally, we modally analyse the derived model via analytical and numerical approaches. The deformable mirror M4 is used to reject wavefront disturbances and enhance the optical imaging quality. We present a control oriented annular sector Kirchhoff–Love plate model featuring an elastic boundary condition and its modal analysis for one of the six identical M4 segments. Subsequently, we show that the well-known method of separation of variables is incompatible with the modal analysis of the presented distributed parameter model in cylindrical coordinates. Moreover, we successfully modally analyse the model using a finite difference approximation and a realistic construction of an M4 segment via a finite element approximation to compare the results. The modal analyses provide consistent results and therefore, both models underlying the analyses are consistent.
期刊介绍:
Mathematical and Computer Modelling of Dynamical Systems (MCMDS) publishes high quality international research that presents new ideas and approaches in the derivation, simplification, and validation of models and sub-models of relevance to complex (real-world) dynamical systems.
The journal brings together engineers and scientists working in different areas of application and/or theory where researchers can learn about recent developments across engineering, environmental systems, and biotechnology amongst other fields. As MCMDS covers a wide range of application areas, papers aim to be accessible to readers who are not necessarily experts in the specific area of application.
MCMDS welcomes original articles on a range of topics including:
-methods of modelling and simulation-
automation of modelling-
qualitative and modular modelling-
data-based and learning-based modelling-
uncertainties and the effects of modelling errors on system performance-
application of modelling to complex real-world systems.