Adaptive Distributed Fuzzy Control for Prescribed-Time Formation of Multiple Autonomous Aerial Vehicles

This study investigated an adaptive distributed prescribed-time fuzzy formation control for quadrotor multi-autonomous aerial vehicles (AAVs). The trajectories of two attitude subsystems were represented through intermediate control variables by considering the underactuated characteristics of AAVs. Furthermore, by utilizing fuzzy logic systems to approximate nonlinear functions and employing the auxiliary function method, this study proposes a distributed adaptive prescribed-time fuzzy formation control scheme. This approach enables real-time updates of the position and speed information for both the leader and follower AAVs. The proposed adaptive prescribed-time fuzzy controller ensures that multi-AAVs reach their formation positions within a prescribed time and that attitude angles can track the reference signals. Finally, the effectiveness of the proposed scheme was verified through a simulation example.

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Publication Details

Journal
IEEE Transactions on Aerospace and Electronic Systems
Published
2024-09-10
DOI
https://doi.org/10.1109/taes.2024.3456756
Citations
13
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
4.54

Funders

Controls
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article

Adaptive Distributed Fuzzy Control for Prescribed-Time Formation of Multiple Autonomous Aerial Vehicles

Dongyang Jin, Zhengrong Xiang, Choon Ki Ahn
13 citations
IEEE Transactions on Aerospace and Electronic Systems
Distributed Control Multi-Agent Systems
4.54
article

Adaptive Distributed Fuzzy Control for Prescribed-Time Formation of Multiple Autonomous Aerial Vehicles

Dongyang Jin, Zhengrong Xiang, Choon Ki Ahn
article en
13 citations

Abstract

This study investigated an adaptive distributed prescribed-time fuzzy formation control for quadrotor multi-autonomous aerial vehicles (AAVs). The trajectories of two attitude subsystems were represented through intermediate control variables by considering the underactuated characteristics of AAVs. Furthermore, by utilizing fuzzy logic systems to approximate nonlinear functions and employing the auxiliary function method, this study proposes a distributed adaptive prescribed-time fuzzy formation control scheme. This approach enables real-time updates of the position and speed information for both the leader and follower AAVs. The proposed adaptive prescribed-time fuzzy controller ensures that multi-AAVs reach their formation positions within a prescribed time and that attitude angles can track the reference signals. Finally, the effectiveness of the proposed scheme was verified through a simulation example.

IEEE Transactions on Aerospace and Electronic SystemsVol. 61(2)
Korea University (KR), Nanjing University of Science and Technology (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 5%
Distributed Control Multi-Agent Systems
4.54
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