Modern 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 |