Izvorni znanstveni članak
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
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
Datum izdavanja:
11.6.2018.
Posjeta: 1.559 *