Dynamic Target Tracking of Unmanned Aerial Vehicles Under Unpredictable Disturbances
Yanjie Chen,
Yangning Wu,
Limin Lan,
Hang Zhong,
Zhiqiang Miao,
Hui Zhang,
Yaonan Wang
Affiliations
Yanjie Chen
School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, China; Department of Computer Science, Aberystwyth University, Aberystwyth SY23 3DB, UK; National Engineering Research Center of Robot Visual Perception and Control Technology, Hunan University, Changsha 410082, China
Yangning Wu
School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, China
Limin Lan
School of Mechanical Engineering and Automation, Fuzhou University, Fuzhou 350108, China
Hang Zhong
School of Robotics, Hunan University, Changsha 410082, China; National Engineering Research Center of Robot Visual Perception and Control Technology, Hunan University, Changsha 410082, China
Zhiqiang Miao
College of Electrical and Information Engineering, Hunan University, Changsha 410082, China; National Engineering Research Center of Robot Visual Perception and Control Technology, Hunan University, Changsha 410082, China
Hui Zhang
School of Robotics, Hunan University, Changsha 410082, China; National Engineering Research Center of Robot Visual Perception and Control Technology, Hunan University, Changsha 410082, China
Yaonan Wang
College of Electrical and Information Engineering, Hunan University, Changsha 410082, China; National Engineering Research Center of Robot Visual Perception and Control Technology, Hunan University, Changsha 410082, China; Corresponding author.
This study proposes an image-based visual servoing (IBVS) method based on a velocity observer for an unmanned aerial vehicle (UAV) for tracking a dynamic target in Global Positioning System (GPS)-denied environments. The proposed method derives the simplified and decoupled image dynamics of underactuated UAVs using a constructed virtual camera and then considers the uncertainties caused by the unpredictable rotations and velocities of the dynamic target. A novel image depth model that extends the IBVS method to track a rotating target with arbitrary orientations is proposed. The depth model ensures image feature accuracy and image trajectory smoothness in rotating target tracking. The relative velocities of the UAV and the dynamic target are estimated using the proposed velocity observer. Thanks to the velocity observer, translational velocity measurements are not required, and the control chatter caused by noise-containing measurements is mitigated. An integral-based filter is proposed to compensate for unpredictable environmental disturbances in order to improve the anti-disturbance ability. The stability of the velocity observer and IBVS controller is analyzed using the Lyapunov method. Comparative simulations and multistage experiments are conducted to illustrate the tracking stability, anti-disturbance ability, and tracking robustness of the proposed method with a dynamic rotating target.
