Distributed Disturbance‐Observer‐Based Bipartite Formation‐Change Finite‐Time Tracking Control of Networked Multi‐ <scp>UAV</scp>

ABSTRACT Recently, bipartite time‐varying formation‐containment tracking control has become an important topic for the formation control of multi‐agent systems. However, these studies combined the dynamics of leaders and followers with a vector‐described dynamic formation. The specific time‐varying formations are unclear for practical use, the disturbance attenuations are not efficiently tackled, and the unsuitable uses in edge computing occur. To overcome these inappropriate issues, a distributed disturbance observer‐based bipartite formation‐change finite‐time tracking control (DDO‐BFC‐FTC) of networked multi‐UAV is addressed in this work. A virtual leader signal is first transmitted to the leader UAV of the 1st group. The DDO‐BFC‐FTC for the serial connection of leader UAVs is then designed to tackle the dominant dynamics of networked multi‐UAV. The planned poses among multiple leaders can easily result in different formations. Subsequently, the DDO‐BFC‐FTC for the other follower UAVs in each group is designed to maintain the 3D pose with respect to their leader, such that the convex hull spanned by the leader UAVs is achieved. These convex hulls do not have intersections to prevent collisions among groups. Besides the stability analyses, the comparison of simulations for the planned 3D pose with formation change validates the effectiveness and practicality of our approach. The average 3D pose error of Residual RNN‐BFC‐FTC is (0.0198 m, 1.129°), which is slightly better than (0.0199 m, 1.180°) of the proposed control at the expense of 4.16 times the computation time.

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Publication Details

Journal
International Journal of Robust and Nonlinear Control
Published
2025-10-09
DOI
https://doi.org/10.1002/rnc.70207
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Distributed Disturbance‐Observer‐Based Bipartite Formation‐Change Finite‐Time Tracking Control of Networked Multi‐ UAV

Chih‐Lyang Hwang, Hailay Berihu Abebe
International Journal of Robust and Nonlinear Control
Distributed Control Multi-Agent Systems
article

Distributed Disturbance‐Observer‐Based Bipartite Formation‐Change Finite‐Time Tracking Control of Networked Multi‐ UAV

Chih‐Lyang Hwang, Hailay Berihu Abebe
article en

Abstract

ABSTRACT Recently, bipartite time‐varying formation‐containment tracking control has become an important topic for the formation control of multi‐agent systems. However, these studies combined the dynamics of leaders and followers with a vector‐described dynamic formation. The specific time‐varying formations are unclear for practical use, the disturbance attenuations are not efficiently tackled, and the unsuitable uses in edge computing occur. To overcome these inappropriate issues, a distributed disturbance observer‐based bipartite formation‐change finite‐time tracking control (DDO‐BFC‐FTC) of networked multi‐UAV is addressed in this work. A virtual leader signal is first transmitted to the leader UAV of the 1st group. The DDO‐BFC‐FTC for the serial connection of leader UAVs is then designed to tackle the dominant dynamics of networked multi‐UAV. The planned poses among multiple leaders can easily result in different formations. Subsequently, the DDO‐BFC‐FTC for the other follower UAVs in each group is designed to maintain the 3D pose with respect to their leader, such that the convex hull spanned by the leader UAVs is achieved. These convex hulls do not have intersections to prevent collisions among groups. Besides the stability analyses, the comparison of simulations for the planned 3D pose with formation change validates the effectiveness and practicality of our approach. The average 3D pose error of Residual RNN‐BFC‐FTC is (0.0198 m, 1.129°), which is slightly better than (0.0199 m, 1.180°) of the proposed control at the expense of 4.16 times the computation time.

International Journal of Robust and Nonlinear ControlVol. 36(4)
National Taiwan University of Science and Technology (TW), Jackson State University (US)
Openalex Percentile: Top 66%
Distributed Control Multi-Agent Systems
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