Distributed Fuzzy Formation Control for Nonlinear Multiagent Systems Under Communication Delays and Switching Topology

In this article, we study the distributed fuzzy formation control problem for a class of strict-feedback nonlinear multiagent systems (NMASs) under communication delays and jointly connected switching topology. Since the communication between agents is affected by time-varying delay and some agents cannot access the leader's information under jointly connected switching topology, a communication-delay-related distributed formation observer is designed to estimate the leader's information and simultaneously mitigate the effects of communication delays. By using fuzzy logic systems to approximate the unknown functions, the controlled uncertain NMASs are transformed into the strict-feedback parameterized NMASs. Then, based on the designed communication-delay-related distributed formation observer and the backstepping control design theory, a fuzzy adaptive formation control algorithm is proposed. By constructing the Lyapunov functions, it is proved that the designed communication-delay-related distributed formation observer errors converge to zero exponentially and the proposed distributed fuzzy formation control algorithm can ensure that the closed-loop systems are semi-globally uniformly ultimately bounded, with the formation tracking errors converging to an adjustable neighborhood around zero. Finally, we apply the distributed fuzzy formation control scheme to marine surface vehicles (MSV), the simulation results and comparisons with the previous control methods verify its effectiveness.

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Publication Details

Journal
IEEE Transactions on Fuzzy Systems
Published
2024-11-08
DOI
https://doi.org/10.1109/tfuzz.2024.3494832
Citations
11
Primary Topic
Distributed Control Multi-Agent Systems
Type
article
Field-Weighted Citation Impact
3.84

Funders

Controls
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article

Distributed Fuzzy Formation Control for Nonlinear Multiagent Systems Under Communication Delays and Switching Topology

Shaocheng Tong, Haodong Zhou, Yi Zuo
11 citations
IEEE Transactions on Fuzzy Systems
Distributed Control Multi-Agent Systems
3.84
article

Distributed Fuzzy Formation Control for Nonlinear Multiagent Systems Under Communication Delays and Switching Topology

Shaocheng Tong, Haodong Zhou, Yi Zuo
article en
11 citations

Abstract

In this article, we study the distributed fuzzy formation control problem for a class of strict-feedback nonlinear multiagent systems (NMASs) under communication delays and jointly connected switching topology. Since the communication between agents is affected by time-varying delay and some agents cannot access the leader's information under jointly connected switching topology, a communication-delay-related distributed formation observer is designed to estimate the leader's information and simultaneously mitigate the effects of communication delays. By using fuzzy logic systems to approximate the unknown functions, the controlled uncertain NMASs are transformed into the strict-feedback parameterized NMASs. Then, based on the designed communication-delay-related distributed formation observer and the backstepping control design theory, a fuzzy adaptive formation control algorithm is proposed. By constructing the Lyapunov functions, it is proved that the designed communication-delay-related distributed formation observer errors converge to zero exponentially and the proposed distributed fuzzy formation control algorithm can ensure that the closed-loop systems are semi-globally uniformly ultimately bounded, with the formation tracking errors converging to an adjustable neighborhood around zero. Finally, we apply the distributed fuzzy formation control scheme to marine surface vehicles (MSV), the simulation results and comparisons with the previous control methods verify its effectiveness.

IEEE Transactions on Fuzzy SystemsVol. 33(2)
Liaoning University of Technology (CN), Dalian Maritime University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 6%
Distributed Control Multi-Agent Systems
3.84
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