Predefined Time and Prespecified Precision for Bearing-Constrained AAV Swarm

This article presents a bearing-based formation control method for autonomous aerial vehicle (AAV) swarms, allowing users to specify both convergence time and precision in advance. Unlike traditional distance-based methods, which rely on intricate distance measurements, our approach simplifies constraints using bearing information, reducing hardware and sensing requirements. It also eliminates the need to update control commands for each AAV, as formation reconfiguration can be achieved solely by adjusting the motion trajectory of formation leaders. Moreover, the strategy demonstrates enhanced robustness in addressing real-world input constraints. A continuous hyperbolic tangent saturation function and an input saturation compensation system are incorporated, ensuring system convergence and precision while addressing singularity issues. In addition, unlike conventional bearing-based strategies focusing primarily on convergence time, the proposed algorithm enables preset control over both convergence time and precision. Finally, the effectiveness of the proposed approach is validated through several illustrative examples, including a 6-degree-of-freedom (6DoF) quadrotor AAV swarm, highlighting its practical applicability and performance.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Cybernetics
Published
2025-03-05
DOI
https://doi.org/10.1109/tcyb.2025.3539704
Citations
6
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
8.92

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Predefined Time and Prespecified Precision for Bearing-Constrained AAV Swarm

Kang Hao Cheong, Dengxiu Yu, Tao Zhang, Zhen Wang et al.
6 citations
IEEE Transactions on Cybernetics
Distributed Control Multi-Agent Systems
8.92
article

Predefined Time and Prespecified Precision for Bearing-Constrained AAV Swarm

Kang Hao Cheong, Dengxiu Yu, Tao Zhang, Zhen Wang, Yan‐Jun Liu
article en
6 citations

Abstract

This article presents a bearing-based formation control method for autonomous aerial vehicle (AAV) swarms, allowing users to specify both convergence time and precision in advance. Unlike traditional distance-based methods, which rely on intricate distance measurements, our approach simplifies constraints using bearing information, reducing hardware and sensing requirements. It also eliminates the need to update control commands for each AAV, as formation reconfiguration can be achieved solely by adjusting the motion trajectory of formation leaders. Moreover, the strategy demonstrates enhanced robustness in addressing real-world input constraints. A continuous hyperbolic tangent saturation function and an input saturation compensation system are incorporated, ensuring system convergence and precision while addressing singularity issues. In addition, unlike conventional bearing-based strategies focusing primarily on convergence time, the proposed algorithm enables preset control over both convergence time and precision. Finally, the effectiveness of the proposed approach is validated through several illustrative examples, including a 6-degree-of-freedom (6DoF) quadrotor AAV swarm, highlighting its practical applicability and performance.

IEEE Transactions on CyberneticsVol. 55(5)
Northwestern Polytechnical University (CN), Nanyang Technological University (SG), Liaoning University of Technology (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities, National Science Fund for Distinguished Young Scholars
Peace, Justice and strong institutions
Openalex Percentile: Top 3%
Distributed Control Multi-Agent Systems
8.92
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Predefined Time and Prespecified Precision for Bearing-Constrained AAV Swarm — Kang Hao Cheong, Dengxiu Yu, et al. · IEEE Transactions on Cybernetics (2025) | TGRS Research Map | TGRS