简化的鲁棒自适应动态面飞行控制律设计

Design of flight control law based on simplified robust adaptive dynamic surface control

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 flight control law based on simplified robust adaptive dynamic surface control is proposed. The complex problem in the traditional backstepping design which is caused by repeated differentiations of virtual control is eliminated by the dynamic surface control method. Neural networks are used to approximate the aero dynamic parameters uncertainties and external disturbances. Simplified adaptive laws only need the number of on-line update parameters to be equal with the number of uncertain terms. All signals in the close loop are guaranteed to be semi-globally uniformly ultimately bounded. Simulation results for post-stall maneuvering flight demonstrate that, con sidering aerodynamic parameters disturbances and external disturbances, the control law can still accomplish post-stall maneuver very well and guarantee a simpler controller structure and good robustness.