J
Jing-Jing Xiong
Researcher at China Jiliang University
Publications - 15
Citations - 1111
Jing-Jing Xiong is an academic researcher from China Jiliang University. The author has contributed to research in topics: Sliding mode control & Trajectory. The author has an hindex of 8, co-authored 9 publications receiving 828 citations. Previous affiliations of Jing-Jing Xiong include Southeast University.
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Journal ArticleDOI
Second order sliding mode control for a quadrotor UAV.
TL;DR: A method based on second order sliding mode control (2-SMC) is proposed to design controllers for a small quadrotor UAV by using Lyapunov theory, which guarantees that all system state trajectories reach and stay on the sliding surfaces.
Journal ArticleDOI
Position and attitude tracking control for a quadrotor UAV.
Jing-Jing Xiong,En-Hui Zheng +1 more
TL;DR: The obtained simulation results show that the synthesis control method has good performance in terms of position and attitude tracking when faced with external disturbances.
Journal ArticleDOI
Global fast dynamic terminal sliding mode control for a quadrotor UAV
Jing-Jing Xiong,Guo-Bao Zhang +1 more
TL;DR: A control method based on global fast dynamic terminal sliding mode control (TSMC) technique is proposed to design the flight controller for performing the finite-time position and attitude tracking control of a small quadrotor UAV.
Journal ArticleDOI
Discrete-time sliding mode control for a quadrotor UAV
Jing-Jing Xiong,Guobao Zhang +1 more
TL;DR: Based on the kinematic and dynamic model of the quadrotor UAV, extensive simulations are performed to illustrate that the proposed control method has a good performance in terms of stabilization and tracking control.
Journal ArticleDOI
Improved Sliding Mode Control for Finite-Time Synchronization of Nonidentical Delayed Recurrent Neural Networks
TL;DR: An improved sliding mode control approach is presented and it is found that the presented control approach can be conveniently verified and does not need to solve any linear matrix inequality (LMI) to guarantee the finite-time synchronization of delayed recurrent neural networks.