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
2016-01-01
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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.