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Asymptotic attitude tracking of the rotorcraft-based UAV via RISE feedback and NN feedforward

机译:基于RISE反馈和NN前馈的基于旋翼机的无人机的渐近姿态跟踪

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This paper presents an asymptotic attitude tracking controller for a rotorcraft-based unmanned aerial vehicle (RUAV) using the robust integral of the signum of the error(RISE) feedback and neural network (NN) feedforward terms. Usually, the typical NN-based attitude controller guarantees the uniformly ultimately bounded stability. In this study, semi-global asymptotic tracking of the RUAV is guaranteed by the RISE feedback term and NN feedforward term adapted by the projection method. The controller is basically designed by the linear dynamic model inversion method whose model is obtained by the linearization of the nonlinear RUAV model at the hover flight. Then, the uncertainty generated in the linearization is removed by the RISE feedback and NN feedforward terms. The asymptotic tracking of the attitude states is proven with the Lyapunov stability analysis, and a numerical simulation using the nonlinear RUAV model is performed to validate the effectiveness of the proposed controller.
机译:本文提出了一种使用误差信号(RISE)反馈和神经网络(NN)前馈项的鲁棒积分的基于旋翼飞机的无人机(RUAV)的渐近姿态跟踪控制器。通常,典型的基于NN的姿态控制器可确保统一的最终有界稳定性。在这项研究中,RUAV的半全局渐近跟踪由RISE反馈项和由投影方法改编的NN前馈项来保证。控制器基本上是通过线性动态模型反演方法设计的,其模型是通过悬停飞行时的非线性RUAV模型的线性化获得的。然后,通过RISE反馈和NN前馈项消除线性化过程中产生的不确定性。利用Lyapunov稳定性分析证明了姿态状态的渐近跟踪,并使用非线性RUAV模型进行了数值模拟,以验证所提出控制器的有效性。

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