Vision-based Fractional Order Sliding Mode Control for Autonomous Vehicle Tracking by a Quadrotor UAV

Heera Lal Maurya, Archit Krishna Kamath, N. Verma, L. Behera
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引用次数: 4

Abstract

This paper proposes a vision-based sliding mode control technique for autonomous tracking of a moving vehicle by a quadrotor. The proposed vision algorithm estimates the quadrotor’s position relative to moving vehicle using an on-board monocular camera. The relative position is provided as an input to a Fractional Order Sliding mode Controller (FOSMC) which ensures the convergence of the relative position between the moving vehicle and the quadrotor thereby enabling it to track the vehicle effectively. In addition, the proposed controller guarantees robustness towards bounded external disturbances and modelling uncertainties. The proposed vision-based control scheme is implemented using numerical simulations and validated in real-time on the DJI Matrice 100. Theses validations help in gaining into the maximum allowable speed of the moving target for the quadrotor to successfully track the object. This plays a vital role in surveillance operations and intruder chase.
基于视觉的四旋翼无人机自动车辆跟踪分数阶滑模控制
提出了一种基于视觉的滑模控制技术,用于四旋翼飞行器的自动跟踪。提出的视觉算法估计四旋翼相对于移动车辆的位置使用机载单目摄像机。相对位置作为输入提供给分数阶滑模控制器(FOSMC),该控制器确保运动车辆和四旋翼飞行器之间的相对位置收敛,从而使其能够有效地跟踪车辆。此外,所提出的控制器保证了对有界外部干扰和建模不确定性的鲁棒性。采用数值仿真实现了基于视觉的控制方案,并在DJI matrix 100上进行了实时验证。这些验证有助于获得进入移动目标的最大允许速度为四旋翼成功跟踪对象。这在监视行动和追击入侵者中起着至关重要的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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