The modern flight control systems are complex since they have a non-linear nature. Also, modern aerospace vehicles are expected to have non-conventional flight envelopes and, in order to operate in uncertain environments, they must guarantee a high level of robustness and adaptability. A Neural Networks controller can be used in applications with manned or unmanned aerial vehicles. The paper shows the mathematical model for hexacopter dynamics and a comparison between two different technique for stabilization and trajectory control: proportional,integral, derivative controller and real rime system controller based on Neural Networks. Numerical simulations are performed in order to validate both mathematical model and control approaches.

Real-time system based on a Neural Network and PID flight control

COLLOTTA, MARIO;MILAZZO, CRISTINA LUCIA ROSA;PAU, GIOVANNI;RICCIARDELLO, ANGELA
2016

Abstract

The modern flight control systems are complex since they have a non-linear nature. Also, modern aerospace vehicles are expected to have non-conventional flight envelopes and, in order to operate in uncertain environments, they must guarantee a high level of robustness and adaptability. A Neural Networks controller can be used in applications with manned or unmanned aerial vehicles. The paper shows the mathematical model for hexacopter dynamics and a comparison between two different technique for stabilization and trajectory control: proportional,integral, derivative controller and real rime system controller based on Neural Networks. Numerical simulations are performed in order to validate both mathematical model and control approaches.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11387/108731
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