Jian Sun
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Jian Sun has a total of 4 co-authors. Here are the top co-authors by number of shared publications:
- Binfang Cao
Hunan University of Arts and Science湖南文理学院, China
1 shared publication - Jianqi Li
Hunan Provincial Key Laboratory for Control Technology of Distributed Electric Propulsion Aircraft, Changde, China
1 shared publication - Jianquan Lu
School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China
1 shared publication - Xin Li
Jishou UniversityJishou University, China
1 shared publication
Latest Publications
- Open Access
- 30 August 2024
- Published by MDPI AG in Preprints.org
A Novel Robust Hybrid Control Strategy for a Quadrotor Trajectory Tracking Aided with Bioinspired Neural Dynamics
This paper proposes a novel hybrid control strategy for quadrotor unmanned aerial vehicles (UAVs) based on bio-inspired neural dynamics. This strategy addresses the velocity jump issue prevalent in traditional backstepping control and the control signal chattering problem common in traditional sliding mode control. The control system comprises an outer-loop bio-inspired backstepping controller and an inner-loop bio-inspired sliding mode controller, ensuring smooth trajectory tracking even in the presence of external disturbances. The stability of the quadrotor UAV control system is rigorously analyzed using Lyapunov stability theory. Extensive comparative simulation experiments are conducted to assess the robustness and effectiveness of the control system. Results demonstrate superior trajectory tracking performance of the proposed control system compared to other control systems for quadrotor UAVs.
- 30 August 2024
- Published by MDPI AG in Preprints.org
Open AccessA Novel Robust Hybrid Control Strategy for a Quadrotor Trajectory Tracking Aided with Bioinspired Neural Dynamics
This paper proposes a novel hybrid control strategy for quadrotor unmanned aerial vehicles (UAVs) based on bio-inspired neural dynamics. This strategy addresses the velocity jump issue prevalent in traditional backstepping control and the control signal chattering problem common in traditional sliding mode control. The control system comprises an outer-loop bio-inspired backstepping controller and an inner-loop bio-inspired sliding mode controller, ensuring smooth trajectory tracking even in the presence of external disturbances. The stability of the quadrotor UAV control system is rigorously analyzed using Lyapunov stability theory. Extensive comparative simulation experiments are conducted to assess the robustness and effectiveness of the control system. Results demonstrate superior trajectory tracking performance of the proposed control system compared to other control systems for quadrotor UAVs.