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https://doi.org/10.30765/er.38.3.3

Neural networks-based robust adaptive flight path tracking control of large transport

Lv Maolong ; School of Aeronautics and Astronautics Engineering, Air Force Engineering University, Xi'an baling road1,710038, China
Xiuxia Sun ; School of Aeronautics and Astronautics Engineering, Air Force Engineering University, Xi'an baling road1,710038, China
G. Z. Xu ; Chinese people’s Liberation Army
Z. T. Wang ; Chinese people’s Liberation Army


Puni tekst: engleski PDF 921 Kb

str. 268-278

preuzimanja: 370

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Sažetak

For the ultralow altitude airdrop decline stage, many factors such as  actuator nonlinearity, the uncertain atmospheric disturbances, and model  unknown nonlinearity affect the precision of trajectory tracking. A robust  adaptive neural network dynamic surface control method is proposed. The  neural network is used to approximate unknown nonlinear continuous  functions of the model, and a nonlinear robust term is introduced to  eliminate the actuator’s nonlinear modeling error and external disturbances. From Lyapunov stability theorem, it is rigorously proved that all the signals in the closed-loop system are bounded. Simulation results confirm the perfect tracking performance and strong robustness of the proposed method.

Ključne riječi

ultra-low altitude airdrop, actuator input nonlinearity, neural network, adaptive control, dynamic surface control, flight path angle

Hrčak ID:

201150

URI

https://hrcak.srce.hr/201150

Posjeta: 642 *