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A Stochastic Global Identification Framework for Aerospace Vehicles Operating Under Varying Flight States
[article]
2016
arXiv
pre-print
In this work, a novel data-based stochastic global identification framework is introduced for air vehicles operating under varying flight states and uncertainty. In this context, the term global refers to the identification of a model that is capable of representing the system dynamics under any admissible flight state based on data recorded from sample states. The proposed framework is based on stochastic time-series models for representing the system dynamics and aeroelastic response under
arXiv:1612.04896v1
fatcat:fsiou3yimnf7hcdg72mr6pwmre