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Frequency Domain System Identification of a Light Helicopter in Hover

MPS-Authors
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Geluardi,  S
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Nieuwenhuizen,  FM
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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Bülthoff,  HH
Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society;
Max Planck Institute for Biological Cybernetics, Max Planck Society;

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AHS-2014-Geluardi.pdf
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引用

Geluardi, S., Nieuwenhuizen, F., Pollini, L., & Bülthoff, H. (2014). Frequency Domain System Identification of a Light Helicopter in Hover. In 70th American Helicopter Society International Annual Forum (AHS 2014) (pp. 1721-1731). Red Hook, NY, USA: Curran.


引用: https://hdl.handle.net/11858/00-001M-0000-0027-80B0-4
要旨
This paper presents the implementation of a Multi-Input Single-Output fully coupled transfer function model of a civil light helicopter in hover. A frequency domain identification method is implemented. It is discussed that the chosen frequency range of excitation allows to capture some important rotor dynamic modes. Therefore, studies that require coupled rotor/body models are possible. The pitch-rate response with respect to the longitudinal cyclic is considered in detail throughout the paper. Different transfer functions are evaluated to compare the capability to capture the main helicopter dynamic modes. It is concluded that models with order less than 6 are not able to model the lead-lag dynamics in the pitch axis. Nevertheless, a transfer function model of the 4th order can provide acceptable results for handling qualities evaluations. The identified transfer function models are validated in the time domain with different input signals than those used during the identification and show good predictive capabilities. From the results it is possible to conclude that the identified transfer function models are able to capture the main dynamic characteristics of the considered light helicopter in hover.