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EnglishModern aerospace vehicles are expected to have nonconventional flight envelopes and, in order to operate in uncertain environments, they must guarantee a high level of robustness and adaptability. A Neural Networks (NN) controller, with real-time learning capability, can be used in applications with manned or unmanned aerial vehicles. In this paper we propose a real-time system, based on a NN model, in order to control the trajectories of a hexacopter. The paper shows a performance evaluation, through a real experimental testbed, of the proposed approach in terms of error measures and obtained coordinates of the hexacopter.
| Titolo: | A Real-Time System based on a Neural Network Model to Control Hexacopter Trajectories |
| Autori: | |
| Data di pubblicazione: | 2014 |
| Handle: | http://hdl.handle.net/11387/52327 |
| ISBN: | 978-147994749-2 |
| Appare nelle tipologie: | 4.1 Contributo in Atti di convegno |
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http://hdl.handle.net/11387/52327
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