Reinforcement Learning for Helicopter Flight Control

Master thesis (2020)

Authors

B. Helder Aerospace Engineering

Contributors

Marilena Pavel (graduation committee member)
Faculty
Aerospace Engineering, Aerospace Engineering
Copyright: © 2020 Bart Helder
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Published Date

30-04-2020

Language

English

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Faculty

Aerospace Engineering

Abstract

Large-scale helicopters have unique characteristics of maneuverability and low-speed performance compared to fixed-wing aircraft. They can take off and land vertically, hover in place for extended periods of time, and move in all six directions, making them occupy important niches in both military and civil aviation. However, these advantages come at a cost: helicopters are inherently unstable with complicated dynamics, and generally more unsafe than commercial air travel. The fatality rate of non-military helicopters is about 1.44 per 100,000 ight hours [9]. This high number is partially explained by the more risky nature of helicopter missions, but is still considerably high compared to the fatality rate of commercial aviation in general.

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