@inproceedings{ad46e4c31ce2430dae622dfc099a3678,
title = "Helicopter parameter estimation based on a nonlinear physics-based model",
abstract = "In this paper, time domain approaches will be applied to estimate the unknown parameters in a physics-based helicopter model. A nonlinear model structure is developed using the blade element momentum theory. We apply the Output Error Method implementation of the Maximum Likelihood estimation theory to estimate the unknown parameters in the model. This nonlinear model is linearized at hover for linear model analysis. The helicopter under investigation in this study is an unmanned helicopter with intermeshing rotors (synchropter). The test data was generated via automatic maneuver injection. We demonstrate that the proposed method provides promising system identification results by combining a physicsbased model and parameter estimation based on flight test data.",
author = "Barzin Hosseini and Aaron Barth and Manfred Hajek and Florian Holzapfel",
note = "Publisher Copyright: {\textcopyright} 2021, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.; AIAA Science and Technology Forum and Exposition, AIAA SciTech Forum 2021 ; Conference date: 11-01-2021 Through 15-01-2021",
year = "2021",
doi = "10.2514/6.2021-1530",
language = "English",
isbn = "9781624106095",
series = "AIAA Scitech 2021 Forum",
publisher = "American Institute of Aeronautics and Astronautics Inc, AIAA",
pages = "1--15",
booktitle = "AIAA Scitech 2021 Forum",
}