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International Journal of Robust and Nonlinear Control
Article . 2025 . Peer-reviewed
License: Wiley Online Library User Agreement
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Observer‐Based Adaptive Bipartite Time‐Varying Formation‐Containment Tracking for Multi‐Agent Systems

Authors: Xinyu Zhang; Xisheng Zhan; Jie Wu; Tao Han; Huaicheng Yan;

Observer‐Based Adaptive Bipartite Time‐Varying Formation‐Containment Tracking for Multi‐Agent Systems

Abstract

ABSTRACTThis article investigates the bipartite time‐varying formation‐containment (BTVFC) tracking problem of linear multi‐agent systems (MASs) with bounded and unknown inputs for the virtual leader. This article proposes adaptive BTVFC tracking protocols suitable for MASs based on bipartite control. It has been demonstrated that real leaders can realize the expected formation and track the virtual leaders' trajectory, and followers can enter the convex envelope that the leaders cross by utilizing Lyapunov stability. In addition, this article also designs the state observer to observe the states of agents that are difficult to measure in the system. Finally, the validity of the main results in the article was verified through numerical simulations.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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