Prescribed‐Time Attitude Bipartite Consensus Tracking Control for Multi‐UAV Systems

ABSTRACT This article focuses on the prescribed‐time attitude bipartite consensus tracking control problem of multi‐unmanned aerial vehicle (UAV) systems under directed graphs. Currently, in the field of bipartite consensus tracking control, algorithms based on finite‐time stability and fixed‐time stability have been developed. However, existing schemes exhibit significant limitations: finite‐time stability algorithms rely on the system's initial states for convergence time, resulting in insufficient temporal controllability. Fixed‐time stability algorithms involve complex coupling among convergence time, system parameters, and control gains, which prevents arbitrary presetting of the convergence moment. This paper introduces the prescribed‐time stability theory, whose core advantage is the ability to preset the convergence time. To achieve this goal, a novel hybrid distributed observer is first designed to ensure accurate estimation of the leader's states within the prescribed‐time. Based on the observer output, a prescribed‐time sliding mode surface (SMS) and the corresponding tracking control law are constructed to drive the multi‐UAV system to achieve attitude bipartite consensus tracking within the prescribed‐time. The proposed scheme not only guarantees the tracking performance within the prescribed time but also avoids the numerical implementation challenges caused by infinite time‐varying gains in traditional prescribed‐time control. Finally, the effectiveness and feasibility of the proposed method are verified through rigorous theoretical analysis and multiple sets of numerical simulations.

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Publication Details

Journal
International Journal of Robust and Nonlinear Control
Published
2025-12-12
DOI
https://doi.org/10.1002/rnc.70325
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Prescribed‐Time Attitude Bipartite Consensus Tracking Control for Multi‐UAV Systems

Guo‐Ping Jiang, Chaoxu Mu, Yingjiang Zhou, Zhihui Liu et al.
International Journal of Robust and Nonlinear Control
Distributed Control Multi-Agent Systems
article

Prescribed‐Time Attitude Bipartite Consensus Tracking Control for Multi‐UAV Systems

Guo‐Ping Jiang, Chaoxu Mu, Yingjiang Zhou, Zhihui Liu, Leimin Wang
article en

Abstract

ABSTRACT This article focuses on the prescribed‐time attitude bipartite consensus tracking control problem of multi‐unmanned aerial vehicle (UAV) systems under directed graphs. Currently, in the field of bipartite consensus tracking control, algorithms based on finite‐time stability and fixed‐time stability have been developed. However, existing schemes exhibit significant limitations: finite‐time stability algorithms rely on the system's initial states for convergence time, resulting in insufficient temporal controllability. Fixed‐time stability algorithms involve complex coupling among convergence time, system parameters, and control gains, which prevents arbitrary presetting of the convergence moment. This paper introduces the prescribed‐time stability theory, whose core advantage is the ability to preset the convergence time. To achieve this goal, a novel hybrid distributed observer is first designed to ensure accurate estimation of the leader's states within the prescribed‐time. Based on the observer output, a prescribed‐time sliding mode surface (SMS) and the corresponding tracking control law are constructed to drive the multi‐UAV system to achieve attitude bipartite consensus tracking within the prescribed‐time. The proposed scheme not only guarantees the tracking performance within the prescribed time but also avoids the numerical implementation challenges caused by infinite time‐varying gains in traditional prescribed‐time control. Finally, the effectiveness and feasibility of the proposed method are verified through rigorous theoretical analysis and multiple sets of numerical simulations.

International Journal of Robust and Nonlinear ControlVol. 36(6)
Anhui University (CN), Tianjin University (CN), China University of Geosciences (CN), China University of Geosciences (Beijing) (CN), Nanjing University of Posts and Telecommunications (CN)
Openalex Percentile: Top 55%
Distributed Control Multi-Agent Systems
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