Distributed Control of Multiconsensus

Gambuzza, Lucia Valentina; Frasca, Mattia

doi:10.1109/tac.2020.3006820

Cited by 27 publications

(6 citation statements)

References 40 publications

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“…Topology reconstruction method can show solutions more intuitively, introduce optimization methods to simplify the controller and preserve certain properties of topology. Multi-consensus can be formed in original topology network, 45,46 but under the action of cyber-attack, original multi-consensus will be affected and the topology structure will also be destroyed. Considering that the attacked topology cannot be repaired, the design of a multi-consensus recovery topology reconstruction controller should be studied, which can recover original multi-consensus.…”

Section: Literature Reviewmentioning

confidence: 99%

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Multi‐consensus recovery of multi‐agent system with cyber‐attack based on topology reconstruction controller

Zhang

Shan

et al. 2022

Intl J Robust & Nonlinear

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This article considers the multi‐consensus recovery for multi‐agent systems (MASs) when the communication network is under cyber‐attack. For distributed control of multi‐consensus, cyber‐attack will invalidate the communication links and seriously affect information interaction between agents, resulting in the destruction of original multi‐consensus. This article considers the design of a recovery topology reconstruction controller, which can ensure the recoverability of original multi‐consensus under cyber‐attack. First, some properties of multi‐consensus of MAS are analyzed. And the cyber‐attack model with the communication link as the attack location is described. Moreover, in order to ensure the simplification of the controller and maintain weak connectivity of original topology under the premise of recovering multi‐consensus, the topology reconstruction controller is further optimized and an optimization algorithm is proposed. Finally, the feasibility and validity of theoretical results are verified by numerical simulations.

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Section: Literature Reviewmentioning

confidence: 99%

“…Then as to illustrate the design of topology reconstruction controller, the following lemma 46 existing between EEP and the Laplacian matrix of its corresponding digraph is introduced. Lemma 4.…”

Section: Topology Reconstruction Controllermentioning

confidence: 99%

Multi‐consensus recovery of multi‐agent system with cyber‐attack based on topology reconstruction controller

Zhang

Shan

et al. 2022

Intl J Robust & Nonlinear

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“…graph (e.g., Jadbabaie et al (2003); Olfati-Saber et al (2007); Aeyels and De Smet (2010); Ren and Cao (2010); Chen et al (2011); Egerstedt et al (2012); Wang and Lu (2019); Gambuzza and Frasca (2020); Mattioni (2020); Cristofaro and Mattioni (2021)). In case of integrator dynamics, the consensus of the network is dictated by the properties of the underlying graph.…”

Section: Introductionmentioning

confidence: 99%

Cluster partitioning of heterogeneous multi-agent systems

Mattioni

Monaco

2022

Automatica

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This paper investigates the collective behaviors induced by the network interconnection of heterogeneous input-affine singleinput nonlinear systems through a constant but general directed graph. In this sense, we prove that the dynamics of all agents cluster into as many subgroups as the number of cells of the almost equitable partition induced by the communication graph. All agents belonging to the same cell are equally influenced by a new mean-field dynamics which is paradigmatic of the network. The case of a network of pendula illustrates the results through simulations.

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“…In the past decades, scholars have carried out in-depth research on the consensus and multi-consensus [6,7] of the first-order and second-order (linear and nonlinear, homogeneous and heterogeneous [8,9]) MASs under different topologies, time delays, sampleddata, asynchronous and aperiodic communications, time-driven jumps, and have achieved fruitful results [10][11][12][13][14][15]. Subsequently, some scholars extended the classical first-order and second-order MASs to high-order MASs [16][17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Consensus of Fractional-Order Double-Integral Multi-Agent System in a Bounded Fluctuating Potential

2022

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At present, the consensus problem of fractional complex systems has received more attention. However, there is little literature on the consensus problem of fractional-order complex systems under noise disturbance. In this paper, we present a fractional-order double-integral multi-agent system affected by a common bounded fluctuating potential, where the protocol term consists of both the relative position and velocity information of neighboring agents. The consensus conditions of the presented system in the absence of noise are analytically given and verified by a numerical simulation algorithm. Then, the influences of the system order and other system parameters on the consensus of the presented system in the presence of bounded noise are also analyzed. It is found that when compared with the classical integer-order system, the presented fractional-order system has a larger range of consensus parameters and has more rich dynamic characteristics under the action of random noise. Especially, the bounded noise has a promoting effect on the consensus of the presented fractional-order system, while there is no similar phenomenon in the corresponding integer-order system.

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Distributed Control of Multiconsensus

Cited by 27 publications

References 40 publications

Multi‐consensus recovery of multi‐agent system with cyber‐attack based on topology reconstruction controller

Multi‐consensus recovery of multi‐agent system with cyber‐attack based on topology reconstruction controller

Cluster partitioning of heterogeneous multi-agent systems

Consensus of Fractional-Order Double-Integral Multi-Agent System in a Bounded Fluctuating Potential

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