Yuqi Qiao

Yuqi Qiao

*This is an algorithmically generated author record based on publicly available information.

Current Organizations / Institutes

The organizations/institutes from the scholar's latest article


Yuqi Qiao has a total of 4 co-authors. Here are the top co-authors by number of shared publications:

  • Qifeng Zhang

    State Key Laboratory of Robotics and Intelligent Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China

    1 shared publication
  • Qingfeng Yao

    State Key Laboratory of Robotics and Intelligent Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China

    1 shared publication
  • Xiaopeng Lv

    State Key Laboratory of Robotics and Intelligent Systems, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China

    1 shared publication
  • Yunfei Bai

    State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China

    1 shared publication

Latest Publications

  • Open Access

    Gain-Scheduled Sliding Mode Control with Time-Delay Estimation for a Cable-Driven Joint of an Underwater Manipulator

    by Xiaopeng Lv, Yuqi Qiao, Qifeng Zhang, Yunfei Bai, Qingfeng Yao

    Using cable transmission in underwater manipulators helps to reduce the mass and rotational inertia of distal moving components, but the control performance of cable-driven joints is affected by flexible cable transmission, equivalent joint-side friction, hydrodynamic effects, and external disturbances. This paper proposes a control method combining time-delay estimation (TDE) with gain-scheduled sliding mode control (GSMC) for a cable-driven joint of an underwater manipulator. TDE uses delayed control-input and joint-acceleration data to estimate and compensate for the lumped dynamic term in the equivalent joint model online. GSMC employs a composite sliding surface and an error-dependent gain-scheduling mechanism to suppress trajectory-tracking errors in the presence of the TDE estimation residual. In joint-level MATLAB/Simulink R2024b simulations, smooth-step, sinusoidal-trajectory-tracking, and ablation results under predefined combined-uncertainty conditions, together with the results of 50 paired Monte Carlo runs, show that TDE-GSMC achieves the lowest major tracking-error indices among the four methods for the smooth-step and 0.35Hz sinusoidal trajectories and also yields the lowest mean tracking error and 95th percentile of the disturbance peak in the Monte Carlo simulations; the ablation results further characterize the performance differences among the tested controller configurations.