超低空空投航迹倾角自适应跟踪控制

针对超低空空投下滑阶段考虑执行器输入死区、不确定性大气扰动以及模型存在未知非线性等因素干扰轨迹精确跟踪等问题,提出了一种自适应神经网络动态面跟踪控制方法.建立了含执行器输入死区的超低空空投载机纵向非线性模型,采用神经网络逼近模型中未知非线性函数,引入非线性鲁棒补偿项消除了执行器死区建模误差和外界扰动.应用Lyapunov稳定性理论证明了闭环系统所有信号均是有界收敛的.仿真验证表明,所提方法既保证了轨迹跟踪的精确性,又具有强鲁棒性.

An adaptive tracking controller for ultra-low altitude airdrop flight path angle

For the ultra-low altitude airdrop decline stage,many factors such as actuator dead-zone,the uncertain atmospheric disturbances and model unknown nonlinearity affect the precision of trajectory tracking,an adaptive neural network dynamic surface control scheme is proposed.The ultra-low altitude airdrop longitudinal dynamics with actuator dead-zone is established,the neural network is used to approximate unknown nonlinear 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 proved that all the signals in the close-loop system are bounded.Simulation results confirm the perfect tracking performance and strong robustness of the proposed method.