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研究一种鲁棒轨迹线性化控制方法并将其应用于无人机(unmanned aerial vehicle,UAV)航迹跟踪控制设计。通过理论分析指明传统轨迹线性化控制方法对系统中的不确定性存在鲁棒性不足的问题,采用改进隐层自适应神经网络对不确定性进行补偿,并利用Lyapunov理论证明了跟踪误差的有界性,最后将该方法应用到无人机三维航迹跟踪控制中。仿真结果表明,当参数摄动在20%时,该控制方法仍能使UAV很好地跟踪理想航迹,从而验证了该方法的有效性。
A robust trajectory linearization control method is studied and applied to the trajectory tracking control design of unmanned aerial vehicle (UAV). The theoretical analysis shows that the traditional trajectory linearization control method has the problem of the lack of robustness to the uncertainties in the system. The improved hidden layer adaptive neural network is used to compensate for the uncertainties. The Lyapunov theory is used to prove that the tracking error has Finally, this method is applied to UAV 3D trajectory tracking control. The simulation results show that the proposed method can still make the UAV track the ideal track well when the parameters are perturbed by 20%, which verifies the effectiveness of the proposed method.