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提出一种简化的鲁棒自适应动态面飞行控制律设计方法。动态面飞行控制律消除了反推设计中由于对虚拟控制反复求导而导致的复杂性问题。利用神经网络在线逼近飞机气动参数的不确定性和外界干扰,简化神经网络参数调整方法,使在线调整更新参数仅为不确定项的个数。基于Lyapunov稳定性定理证明了闭环系统的所有信号半全局一致最终有界。大迎角过失速机动飞行的数值仿真表明:在考虑气动参数摄动和外界干扰的情况下,过失速机动仍很好地实现,且兼具控制器结构简单和鲁棒性强的特点。
A simplified robust adaptive dynamic plane flight control law design method is proposed. The dynamic plane flight control law eliminates the complexity problem caused by repeated derivation of virtual control in the backstepping design. The neural network is used to approximate the uncertainty of the aerodynamic parameters of the aircraft and the external disturbance online, which simplifies the method of parameter adjustment of the neural network so that the online adjustment update parameter is only the number of the uncertain items. Based on the Lyapunov stability theorem, it is proved that all signals in a closed-loop system are semi-globally uniform and ultimately bounded. The numerical simulation of stalling maneuvering flight at high angle of attack shows that the stalling maneuver is still well achieved considering the perturbation of aerodynamic parameters and external disturbances, and the controller has the advantages of simple structure and strong robustness.