Distributed Adaptive Affine Formation Maneuver Control for Multiple AUV Systems via Self-Triggered Mechanism

This article investigates the distributed three-dimensional (3-D) formation maneuver of multiple AUV systems (MAUVSs) under a self-triggered mechanism. The formation achieves flexible 3-D maneuvering through prescribed affine transformations, including translation, rotation, scaling, and shearing. For each AUV, the desired position trajectory is determined by the affine formation structure, while the corresponding desired pitch and yaw angles are generated online from its individual reference trajectory. Based on this framework, a self-triggered mechanism (STM) is introduced into distributed controllers to further reduce data transmission. The proposed STM calculates the subsequent triggering instant using the controller information available at the current trigger, thereby avoiding continuous evaluation of the measurement errors. Furthermore, RBFNN-based uncertainty approximation is incorporated into the controller and stability analysis establishes practical fixed-time convergence of tracking errors under lumped disturbances.

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Publication Details

Journal
Drones
Published
2026-10-28
DOI
https://doi.org/10.3390/drones10110810
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
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article

Distributed Adaptive Affine Formation Maneuver Control for Multiple AUV Systems via Self-Triggered Mechanism

Jiang Shu-kai, Zhuo Wang, Chong Wang, Yingxuan Wang et al.
5 links
Drones
Distributed Control Multi-Agent Systems
article

Distributed Adaptive Affine Formation Maneuver Control for Multiple AUV Systems via Self-Triggered Mechanism

Jiang Shu-kai, Zhuo Wang, Chong Wang, Yingxuan Wang, Meng Lv
article en

Abstract

This article investigates the distributed three-dimensional (3-D) formation maneuver of multiple AUV systems (MAUVSs) under a self-triggered mechanism. The formation achieves flexible 3-D maneuvering through prescribed affine transformations, including translation, rotation, scaling, and shearing. For each AUV, the desired position trajectory is determined by the affine formation structure, while the corresponding desired pitch and yaw angles are generated online from its individual reference trajectory. Based on this framework, a self-triggered mechanism (STM) is introduced into distributed controllers to further reduce data transmission. The proposed STM calculates the subsequent triggering instant using the controller information available at the current trigger, thereby avoiding continuous evaluation of the measurement errors. Furthermore, RBFNN-based uncertainty approximation is incorporated into the controller and stability analysis establishes practical fixed-time convergence of tracking errors under lumped disturbances.

DronesVol. 10(11)
Harbin Engineering University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 12%
Distributed Control Multi-Agent Systems
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