Kunting Yu
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Kunting Yu has a total of 3 co-authors. Here are the top co-authors by number of shared publications:
- Maolong Lv
College of Air Traffic Control and Navigation, Air Force Engineering University, Xian, China
2 shared publications - Shaocheng Tong
Navigation College Dalian Maritime University Dalian China
2 shared publications - Yongming Li
Liaoning University of Technology
2 shared publications
Latest Publications
- 7 May 2024
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Intelligent Vehicles
- Vol. 9 (11) , 7476-7484
Adaptive Backstepping Control for Underactuated 6-DoF USV With Uncertain Dynamics
This paper introduces a target tracking control approach for an underactuated Unmanned Surface Vehicle (USV) with 6 Degrees of Freedom (6-DoF), characterized by unknown dynamics and disturbances. Notably, the system inertia matrix of this 6-DoF USV is positive definite and non-diagonal, implying the presence of intricate coupling relationships within the input vector components. To address the challenges posed by underactuation, we present an adaptive control methodology utilizing a novel transverse function and backstepping procedure. Furthermore, we introduce a dynamic signal to compensate for external dynamic uncertainties and disturbances. Leveraging Lyapunov stability theory, we establish that the target tracking error converges to a small neighborhood near the origin, and all signals within the closed-loop system remain bounded. Lastly, we showcase the effectiveness of the proposed control methodology through simulation results involving a 6-DoF supply vehicle.
- 7 May 2024
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Intelligent Vehicles
- Vol. 9 (11) , 7476-7484
Adaptive Backstepping Control for Underactuated 6-DoF USV With Uncertain Dynamics
This paper introduces a target tracking control approach for an underactuated Unmanned Surface Vehicle (USV) with 6 Degrees of Freedom (6-DoF), characterized by unknown dynamics and disturbances. Notably, the system inertia matrix of this 6-DoF USV is positive definite and non-diagonal, implying the presence of intricate coupling relationships within the input vector components. To address the challenges posed by underactuation, we present an adaptive control methodology utilizing a novel transverse function and backstepping procedure. Furthermore, we introduce a dynamic signal to compensate for external dynamic uncertainties and disturbances. Leveraging Lyapunov stability theory, we establish that the target tracking error converges to a small neighborhood near the origin, and all signals within the closed-loop system remain bounded. Lastly, we showcase the effectiveness of the proposed control methodology through simulation results involving a 6-DoF supply vehicle.
- 23 January 2024
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Artificial Intelligence
- Vol. 5 (8) , 4058-4073
Distributed Optimal Formation Control of Multiple Unmanned Surface Vehicles With Stackelberg Differential Graphical Game
In this work, a cooperative formation control methodology is proposed for multiple six-degree-of-freedom (6-DoF) unmanned surface vehicles (USVs) subject to input saturation. Our method includes several key steps. To begin, we formulate the optimal formation control problem for USVs as Stackelberg differential graphical games. According to this design principle, each USV is partitioned into a primary follower and a secondary follower. The primary followers coalesce into one team, while the secondary followers constitute another team independently. Secondly, a new type of barrier Lyapunov function (BLF) with a hyperbolic tangent function is introduced to indirectly constrain velocity vector. Thirdly, an auxiliary system is established to compensate for the input saturation. Then the Lyapunov stability theory is employed to prove that all closed-loop signals of multiple USVs are semi-global uniform ultimate boundedness (SGUUB). Finally, we present the simulation results of our proposed control scheme. These results demonstrate the effectiveness and feasibility of our proposed methodology for cooperative formation control of multiple USVs.
- 23 January 2024
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Artificial Intelligence
- Vol. 5 (8) , 4058-4073
Distributed Optimal Formation Control of Multiple Unmanned Surface Vehicles With Stackelberg Differential Graphical Game
In this work, a cooperative formation control methodology is proposed for multiple six-degree-of-freedom (6-DoF) unmanned surface vehicles (USVs) subject to input saturation. Our method includes several key steps. To begin, we formulate the optimal formation control problem for USVs as Stackelberg differential graphical games. According to this design principle, each USV is partitioned into a primary follower and a secondary follower. The primary followers coalesce into one team, while the secondary followers constitute another team independently. Secondly, a new type of barrier Lyapunov function (BLF) with a hyperbolic tangent function is introduced to indirectly constrain velocity vector. Thirdly, an auxiliary system is established to compensate for the input saturation. Then the Lyapunov stability theory is employed to prove that all closed-loop signals of multiple USVs are semi-global uniform ultimate boundedness (SGUUB). Finally, we present the simulation results of our proposed control scheme. These results demonstrate the effectiveness and feasibility of our proposed methodology for cooperative formation control of multiple USVs.