Bipartite Consensus of Linear Multi-Agent Systems by Distributed Event-Triggered Control

Yang, Ruitian; Yang, Yongqing; Zhu, Fengzeng

doi:10.1007/s11424-020-9293-7

Cited by 16 publications

(4 citation statements)

References 31 publications

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“…In fact, the two relationships, collaboration and antagonism, coexist among agents in natural or engineering scenarios. 47 For example, in the multi-robot systems, the relationship between a robot and its teammates is collaborative, but between it and its antagonistic alliance’s robots are antagonistic. In biological systems, a pair of genes are viewed as activators when they are in cooperative interaction and inhibitors when in competitive interactions.…”

Section: Introductionmentioning

confidence: 99%

Data-based bipartite formation control for multi-agent systems with communication constraints

Wang,

Zhao,

et al. 2024

Science Progress

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This article investigates data-driven distributed bipartite formation issues for discrete-time multi-agent systems with communication constraints. We propose a quantized data-driven distributed bipartite formation control approach based on the plant’s quantized and saturated information. Moreover, compared with existing results, we consider both the fixed and switching topologies of multi-agent systems with the cooperative-competitive interactions. We establish a time-varying linear data model for each agent by utilizing the dynamic linearization method. Then, using the incomplete input and output data of each agent and its neighbors, we construct the proposed quantized data-driven distributed bipartite formation control scheme without employing any dynamics information of multi-agent systems. We strictly prove the convergence of the proposed algorithm, where the proposed approach can ensure that the bipartite formation tracking errors converge to the origin, even though the communication topology of multi-agent systems is time-varying switching. Finally, simulation and hardware tests demonstrate the effectiveness of the proposed scheme.

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Section: Introductionmentioning

confidence: 99%

Data-based bipartite formation control for multi-agent systems with communication constraints

Wang,

Zhao,

et al. 2024

Science Progress

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“…However, in practice, MASs with competitive relationship are also common in social networks, chaotic systems, and other fields. In recent years, bipartite consensus has attracted extensive attention for cooperative and competitive MASs, in which the mutual interactions can be described by a weighted and signed network [8]. Bipartite consensus means that the states of all agents can converge to consensus values, which are identical in modulus, but different in sign [9].…”

Section: Introductionmentioning

confidence: 99%

Bipartite consensus of linear multi‐agent systems with intermittent event‐triggered protocols

Zhao,

Liu,

Wang

2023

Math Methods in App Sciences

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In this paper, bipartite consensus of linear multi‐agent systems with structually balanced signed network is investigated. In particularly, control protocols for consensus are considered to work under an intermittent framework due to some unavoidable factors. Meanwhile, the event‐triggered mechanism is introduced in order to reduce the update frequency of control input. Based on distributed intermittent event‐triggered control, some sufficient conditions are proposed to ensure leaderless and leader‐following bipartite consensus. Moreover, minimum event‐triggered intervals are set to be positive in advance to exclude Zeno behavior. Finally, two numerical examples are provided to verify the effectiveness of theoretical results.

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“…As one of the basic problems of multi‐agent systems (MASs), cooperative control has received increasing attention 1‐18 . In Reference 13, the distributed synchronization control problem for a class of uncertain nonlinear leader‐following systems with unknown backlash‐like hysteresis was studied on a directed graph.…”

Section: Introductionmentioning

confidence: 99%

“…As one of the basic problems of multi-agent systems (MASs), cooperative control has received increasing attention. [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18] In Reference 13, the distributed synchronization control problem for a class of uncertain nonlinear leader-following systems with unknown backlash-like hysteresis was studied on a directed graph. In Reference 15, an adaptive control strategy based on fully distributed neural network (NN) was designed, and the cooperative control problem of nonlinear MASs with unmodeled dynamics was solved, which ensured that all followers can asymptotically synchronize to the leader, and the synchronization errors were within the specified level.…”

Section: Introductionmentioning

confidence: 99%

Command filtered fixed‐time control for a class of multi‐agent systems with sensor faults

Dong

Yao

et al. 2021

Intl J Robust & Nonlinear

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In this article, the command filtered fixed‐time fault‐tolerant control (FTC) problem is investigated for multi‐agent systems (MASs). The considered MASs with nonstrict feedback form are affected by unknown nonlinear functions and sensor faults, which are solved by using the properties of neural networks (NNs). In the design process, in order to avoid the “singularity” and “explosion of complexity” problems, an adaptive command filtered fixed‐time NN fault‐tolerant controller is devised. Based on the Lyapunov stability theory, all output signals of leader and followers in the closed‐loop system are synchronized within fixed time. Finally, the effectiveness of the proposed control scheme is verified by simulation experiments.

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Bipartite Consensus of Linear Multi-Agent Systems by Distributed Event-Triggered Control

Cited by 16 publications

References 31 publications

Data-based bipartite formation control for multi-agent systems with communication constraints

Data-based bipartite formation control for multi-agent systems with communication constraints

Bipartite consensus of linear multi‐agent systems with intermittent event‐triggered protocols

Command filtered fixed‐time control for a class of multi‐agent systems with sensor faults

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