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Vision-based trajectory tracking control of quadrotors using super twisting sliding mode control

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  • Wenhui Wu
  • Xin Jin
  • Yang Tang

Abstract

A trajectory-tracking problem for a vision-based quadrotor control system is investigated in this paper. A super twisting sliding mode (STSM) controller is proposed for finite-time trajectory tracking control. With the help of the homogeneous technique, the closed-loop system is proved to be finite-time stable. In addition, due to the introduction of super twisting mechanism, the controller can restrain chattering effect of sliding mode control. On the other hand, a pose estimation through data fusion is proposed to localise the quadrotor. A Kalman filter (KF) is utilised to fuse the estimated pose from semi-direct monocular visual odometry (SVO) with data from inertial measurement unit (IMU). A number of simulations are carried out on MATLAB and physical engine simulator Gazebo. The results show that the proposed system controller has better performances in terms of robustness and anti-disturbance than the proportional–integral–derivative (PID) controller and the first order sliding mode controller.

Suggested Citation

  • Wenhui Wu & Xin Jin & Yang Tang, 2020. "Vision-based trajectory tracking control of quadrotors using super twisting sliding mode control," Cyber-Physical Systems, Taylor & Francis Journals, vol. 6(4), pages 207-230, October.
    • Handle: RePEc:taf:tcybxx:v:6:y:2020:i:4:p:207-230
    DOI: 10.1080/23335777.2020.1727960
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    Cited by:

    1. Luis Felipe Muñoz Mendoza & Guillermo García-Torales & Cuauhtémoc Acosta Lúa & Stefano Di Gennaro & José Trinidad Guillen Bonilla, 2023. "Trajectories Generation for Unmanned Aerial Vehicles Based on Obstacle Avoidance Located by a Visual Sensing System," Mathematics, MDPI, vol. 11(6), pages 1-25, March.

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