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Model-based optimal auto-transition and control synthesis for tail-sitter UAV KH-Lion

机译:尾座无人机KH-Lion基于模型的最优自动过渡和控制综合

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This paper presents a systematic control synthesis method in order to achieve auto-transition for KH-Lion, a tail-sitter hybrid UAV. Although there are huge potentials in various applications of the hybrid tail-sitter UAVs, the transition between vertical take-off and landing mode and cruise mode is still a challenge now. Due to the complex behaviour that the transition can generate, it is very difficult to implement the auto-transition as the reference transition trajectory is hard to obtain. In this paper, we propose to use the model validated from the experiments to generate an optimal reference trajectory for transition. A constrained dynamic programming technique is applied to the model with the consideration of all necessary constraints. A feedback control algorithm is also designed to track the desired transition trajectory. Simulation result and successful flight experiments have demonstrated the effectiveness of the proposed synthesis method.
机译:本文提出了一种系统的控制综合方法,以实现后置混合动力无人机KH-Lion的自动转换。尽管混合式尾座无人机的各种应用都有巨大的潜力,但垂直起降模式和巡航模式之间的过渡现在仍然是一个挑战。由于过渡可能会产生复杂的行为,因此很难实现自动过渡,因为很难获得参考过渡轨迹。在本文中,我们建议使用通过实验验证的模型来生成过渡的最佳参考轨迹。考虑到所有必要约束,将约束动态编程技术应用于模型。还设计了一种反馈控制算法来跟踪所需的过渡轨迹。仿真结果和成功的飞行实验证明了所提方法的有效性。

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