Paper
5 July 2024 Prescribed-time formation control of multiple underactuated autonomous surface vehicles bearing-only and single distance measurement
Yuan Wang, Jiafeng Zheng
Author Affiliations +
Proceedings Volume 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024); 131846W (2024) https://doi.org/10.1117/12.3033081
Event: 3rd International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 2024, Kuala Lumpur, Malaysia
Abstract
This study investigates the formation control problem of underactuated unmanned surface vehicles based on azimuth information. A formation control algorithm with a Prescribed-time convergence is proposed, where the control law is based on time-varying gains, and the convergence time can be arbitrarily chosen by the user. The "Leader-First follower" formation control structure is adopted, where only the first follower can measure the distance and azimuth of the leading vessel, while the remaining followers can only measure the relative azimuth with respect to their neighbors. For the first follower, a control algorithm based on distance and relative azimuth is designed, allowing it to follow the moving leading vessel, and the tracking error can converge within a Prescribed-time. For the remaining followers, a control law using only azimuth information is proposed, enabling them to achieve formation within a Prescribed-time based solely on relative azimuth information. The construction of a Lyapunov function is employed to prove that the control laws can achieve convergence of the unmanned surface vehicle formation system within the Prescribed-time. Finally, the effectiveness of the algorithm is verified through numerical simulation experiments.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
Yuan Wang and Jiafeng Zheng "Prescribed-time formation control of multiple underactuated autonomous surface vehicles bearing-only and single distance measurement", Proc. SPIE 13184, Third International Conference on Electronic Information Engineering and Data Processing (EIEDP 2024), 131846W (5 July 2024); https://doi.org/10.1117/12.3033081
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KEYWORDS
Autonomous vehicles

Distance measurement

Matrices

Control systems

Magnetic resonance imaging

Design

Detection and tracking algorithms

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