Artificial Potential Field-Based Multi-UAV Formation Control and Target Tracking

Song, He; Hu, Shaolin; Jiang, Wenqiang; Guo, Qiliang; Zhu, Ming

doi:10.1155/2022/4253558

Cited by 4 publications

(2 citation statements)

References 32 publications

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“…As an extension of single-USV trajectory tracking control, multiple-USV cooperative trajectory tracking control limits the positioning among USVs by setting the desired navigation trajectory for each USV in advance, thus significantly reducing the task completion time and demonstrating advantages such as high accuracy and robustness. The cooperative trajectory tracking control scenario can be implemented using the formation control framework, and typical formation strategies include leader-follower formation framework, artificial potential field, behavior-based, virtual structure, and graph theory [4][5][6][7][8]. Specifically, a distributed prescribed-time leader-follower formation control scheme for SUV in [4], while meeting the predefined transient performance and overcoming the unknowns and input saturation.…”

Section: Introductionmentioning

confidence: 99%

“…Specifically, a distributed prescribed-time leader-follower formation control scheme for SUV in [4], while meeting the predefined transient performance and overcoming the unknowns and input saturation. In [5], the artificial potential function consisting of formation control term and target tracking term is established for multiple unmanned aerial vehicles, which achieves accurate formation. Considering the problems of unreachable targets and local minimums in artificial potential fields, ref.…”

Section: Introductionmentioning

confidence: 99%

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Trajectory Tracking Control of Unmanned Surface Vehicles Based on a Fixed-Time Disturbance Observer

et al. 2023

Electronics

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In ocean environments with unknown complex disturbances, the control accuracy for an unmanned surface vehicle (USV) is severely challenged with an increase in task complexity. As the foundation for executing complex tasks, it is particularly important to control a USV to navigate along a safe trajectory that has been set. In order to effectively handle the trajectory tracking problem, an innovative USV tracking control strategy with high accuracy is proposed by combining the integral sliding-mode and disturbance observer technologies, and these are effectively extended to a scenario with the cooperative trajectory tracking of multiple USVs in this study. Specifically, unknown disturbances are treated as lumped uncertainties, and a novel fixed-time stable-convergence disturbance observer (FT-DO) is proposed to effectively observe and approximate the lumped uncertainties. Then, in order to quickly reach and steadily navigate along the desired trajectory, an effective fixed-time stable-convergence fast integral sliding mode is modified, and on this basis, an accurate trajectory tracking controller (FTFISM-TTC) for a single USV and a cooperative trajectory tracking controller for multiple USVs are meaningfully proposed. Finally, the stability of FT-DO and FTFISM-TTC was rigorously proven by using the Lyapunov approach, and a comprehensive simulation of current advanced tracking control methods was conducted by using Matlab, which proved the reliability of the proposed trajectory tracking control strategy and further eliminated the impact of the initial state on the tracking accuracy.

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