Adaptive Formation Control for Underactuation Multi-USVs with Jointly Connected Switching Typologies*

This paper investigates the adaptive formation control problem for underactuation Multiply Unmanned Surface Ve-hicles (multi- USV s) connected by the jointly connected switching typologies. First, the distributed switching observer is devised for each USV to estimate the trajectory signal under the jointly connected switching typologies. Secondly, the underactuation controllers are designed based on the estimated trajectory signal under backstepping structure. In the form of the designed underactuated controller, we have proven through Lyapunov stability theory that each unmanned vessel is able to track the predetermined trajectory. In the end, we validate the effectiveness of the proposed method through numerical simulations.

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Publication Details

Published
2024-12-06
DOI
https://doi.org/10.1109/icist63249.2024.10805413
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Adaptive Formation Control for Underactuation Multi-USVs with Jointly Connected Switching Typologies*

Kunting Yu, Kewen Li, Yongming Li
Distributed Control Multi-Agent Systems
article

Adaptive Formation Control for Underactuation Multi-USVs with Jointly Connected Switching Typologies*

Kunting Yu, Kewen Li, Yongming Li
article en

Abstract

This paper investigates the adaptive formation control problem for underactuation Multiply Unmanned Surface Ve-hicles (multi- USV s) connected by the jointly connected switching typologies. First, the distributed switching observer is devised for each USV to estimate the trajectory signal under the jointly connected switching typologies. Secondly, the underactuation controllers are designed based on the estimated trajectory signal under backstepping structure. In the form of the designed underactuated controller, we have proven through Lyapunov stability theory that each unmanned vessel is able to track the predetermined trajectory. In the end, we validate the effectiveness of the proposed method through numerical simulations.

Liaoning University of Technology (CN), Dalian Maritime University (CN)
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Openalex Percentile: Top 72%
Distributed Control Multi-Agent Systems
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