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Conference Paper

Augmented Systems for a Personal Aerial Vehicle Using a Civil Light Helicopter Model

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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Citation

Geluardi, S., Nieuwenhuizen, F., Pollini, L., & Bülthoff, H. (2015). Augmented Systems for a Personal Aerial Vehicle Using a Civil Light Helicopter Model. In 71st American Helicopter Society International Annual Forum (AHS 2015) (pp. 1428-1436). Red Hook, NY, USA: Curran.


Cite as: https://hdl.handle.net/11858/00-001M-0000-002A-4654-F
Abstract
This paper presents the implementation of classic augmented control stategies applied to an identified civil light heli-
copter model in hover. Aim of this study is to enhance the stability and controllability of the helicopter model and to
improve its Handling Qualities (HQs) in order to meet those defined for a new category of aircrafts, Personal Aerial
Vehicles (PAVs). Two control methods were used to develop the augmented systems, H-control and m-synthesis. The
resulting augmented systems were compared in terms of achieved robust stability, nominal performance and robust
performance. The robustness was evaluated against parametric uncertainties and external disturbances modeled as real atmospheric turbulences that might be experienced in hover and low speed flight. The main result achieved in
this work is that classical control techniques can augment a linear helicopter model to match PAVs responses at low
frequencies. As a consequence, the achieved HQs performance resemble those defined for PAVs pilots. However, both control techniques performed poorly for some specific uncertainty conditions demonstrating unsatisfactory per-
formance robustness. Differences, advantages and limitations of the implemented control architectures with respect to the considered requirements are described in the paper.