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Fractional order robust visual servoing control of a quadrotor UAV with larger sampling period

机译:具有更大采样周期的四旋翼无人机的分数阶鲁棒视觉伺服控制

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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 proportional-integral-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:由于其体积小,成本低且易于维护,无人机已广泛应用于民用和军事领域,例如救援,监视,勘探,导航,精确农业等。然而,在非结构化环境下无人机的自主飞行仍然是开放的,特别是在GPS不可用或已安排室内任务时。此外,需要提高基于GPS的导航精度。为了解决这些限制,在本文中,我们提供了一种基于工程的解决方案,该解决方案基于视觉伺服和无GPS信息的分数阶比例积分-微分(PID)控制器,提供了一种精确的悬停解决方案。首先,通过阶跃响应实验获得了四轴飞行器的数学速度模型。然后,设计分数阶PID控制器算法以提高其悬停精度和鲁棒性。在我们的工作中,使用基于机载颜色的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均表明,该方案在悬停精度和对干扰的鲁棒性方面可以实现更好的性能。特别是,我们首次展示了使用分数阶控制算法时的采样周期可能会比平时更长,从而放宽了对基于实时实时视觉的反馈的昂贵硬件要求。

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