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EnglishModern aerospace vehicles are expected to have non-conventional flight envelopes and then, in order to operate in uncertain environments, they must guarantee a high level of robustness and adaptability. A Neural Network (NN) controller, with real-time learning capability, can be used in applications with manned or unmanned aerial vehicles. In this paper a novel real-time control system, based on a NN model, in order to control the trajectories of a hexacopter is proposed. The proposed NN is optimized by the analytical calculation of the embedding parameters. The paper shows a performance evaluation, through a real experimental testbed, of the proposed approach in terms of error measures and computation of the angular velocities of the hexacopter.
| Titolo: | An Integrated System for UAV Control Using a Neural Network Implemented in a Prototyping Board | |
| Autori: | ||
| Data di pubblicazione: | 2016 | |
| Rivista: | ||
| Handle: | http://hdl.handle.net/11387/116498 | |
| Appare nelle tipologie: | 1.1 Articolo in rivista |
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http://hdl.handle.net/11387/116498
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