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Fractional Order Robust Visual Servoing Control of A Quadrotor UAV with Larger Sampling Period

机译:具有较大抽样周期的分数秩序强大的伺服控制四轮车UAV

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Unmanned aerial vehicles (UAVs) are widely applied in both civil and military fields, such as rescue, surveillance, exploration, navigation, precision agriculture and etc., because of small size, low cost and easy maintenance. However the autonomous flight of UAVs under unstructured environment is still open, especially when GPS is unavailable or indoor task is scheduled. Furthermore, GPS-based navigation accuracy needs to be improved. To deal with these limitations, in this paper, we provide an engineering-oriented solution of precise hovering based on visual servoing and fractional order proportionalintegral-derivative (PID) controller without GPS information. First, the mathematical speed model of a quadcopter is obtained by step response experiments. Then, fractional order PID controller algorithm is designed to improve its hovering accuracy and robustness. In our work, the position reference is extracted with an on-board color based target recognition algorithm instead of GPS. Both simulation and field experimental results demonstrate that the proposed scheme can achieve a better performance in terms of hovering accuracy and robustness to disturbances. In particular, for the first time, we show that, the sampling period can be bigger than usual when using fractional order control algorithm, relaxing costly hardware requirement for fast real-time vision-based feedback.
机译:无人驾驶航空公司(无人机)广泛应用于民间和军事领域,如救援,监控,勘探,导航,精密农业等,因为尺寸小,成本低,维护方便。然而,非结构化环境下的无人机自主飞行仍然是开放的,特别是当GPS不可用或安排室内任务时。此外,需要改善基于GPS的导航精度。为了处理这些限制,在本文中,我们提供了一种基于视觉伺服和分数阶数的精确悬停的有针对性的解决方案,而不是GPS信息的基于视觉伺服和分数比例的integlal-衍生物(PID)控制器。首先,通过步骤响应实验获得Quadcopter的数学速度模型。然后,旨在提高其悬停的精度和鲁棒性的分数级PID控制器算法。在我们的工作中,通过基于板上的彩色目标识别算法而不是GPS提取位置参考。仿真和现场实验结果都表明,该方案可以在悬停精度和稳健性方面实现更好的性能。特别是,我们首次表明,采样时期可以比平常更大,当使用分数阶控制算法时,放松昂贵的硬件要求,以快速实时视觉的反馈。

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