论文标题
使用经常性神经网络对尾声无人机的过渡控制
Transition control of a tail-sitter UAV using recurrent neural networks
论文作者
论文摘要
本文介绍了基于反复的神经网络（RNN）控制器的实施，以稳定飞行过渡动作（悬停裁缝，反之亦然），无用的尾声。控制策略基于态度和速度稳定。为此，RNN用于在过渡阶段估计高非线性空气动力学项。然后，该估计与反馈线性化技术一起使用，以稳定整个系统。结果表明线性速度和过渡动作过程中的螺距角的收敛性。为了分析我们提出的控制策略的性能，我们为从悬停到巡航的过渡提供了模拟，反之亦然。
This paper presents the implementation of a Recurrent Neural Network (RNN) based-controller for the stabilization of the flight transition maneuver (hover-cruise and vice versa) of a tail-sitter UAV. The control strategy is based on attitude and velocity stabilization. For that aim, the RNN is used for the estimation of high nonlinear aerodynamic terms during the transition stage. Then, this estimate is used together with a feedback linearization technique for stabilizing the entire system. Results show convergence of linear velocities and the pitch angle during the transition maneuver. To analyze the performance of our proposed control strategy, we present simulations for the transition from hover to cruise and vice versa.
