A survey of the consensus for multi-agent systems

Li, Yanjiang; Tan, Chong

doi:10.1080/21642583.2019.1695689

Cited by 72 publications

(33 citation statements)

References 163 publications

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“…Note that the controller is distributed in the sense that each agent requires only relative position and velocity measurements of its neighboring agents. Note that, differently from discontinuous signed finite-time nonlinear protocols [19], [20], here we design a homogeneous continuous protocol aimed at avoiding undesirable chattering in the closed-loop trajectories arising from the existence of discontinuous control actions.…”

Section: Design Of the Finite-time Distributedmentioning

confidence: 99%

Cooperative Intersection Crossing Over 5G

Castiglione

Falcone

Petrillo

et al. 2021

IEEE/ACM Trans. Networking

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Autonomous driving is a safety critical application of sensing and decision-making technologies. Communication technologies extend the awareness capabilities of vehicles, beyond what is achievable with the on-board systems only. Nonetheless, issues typically related to wireless networking must be taken into account when designing safe and reliable autonomous systems. The aim of this work is to present a control algorithm and a communication paradigm over 5G networks for negotiating traffic junctions in urban areas. The proposed control framework has been shown to converge in a finite time and the supporting communication software has been designed with the objective of minimizing communication delays. At the same time, the underlying network guarantees reliability of the communication. The proposed framework has been successfully deployed and tested, in partnership with Ericsson AB, at the AstaZero proving ground in Goteborg, Sweden. In our experiments, three heterogeneous autonomous vehicles successfully drove through a 4-way intersection of 235 square meters in an urban scenario.

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Section: Design Of the Finite-time Distributedmentioning

confidence: 99%

Cooperative Intersection Crossing Over 5G

Castiglione

Falcone

Petrillo

et al. 2021

IEEE/ACM Trans. Networking

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“…Multi-agent decision-making is a wide field ( [11,12]). One of the main challenges in multi-agent decision-making is designing mechanisms for the group to reach an agreement, i.e., consensus [13][14][15]. Voting is a central mechanism for reaching an agreement ( [16]).…”

Section: Related Workmentioning

confidence: 99%

Decision-Making under Group Commitment

Kalech¹

2021

Mathematics

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Coordination is essential for establishing and sustaining teamwork. Agents in a team must agree on their tasks and plans, and thus, group decision-making techniques are necessary to reach agreements in teams. For instance, to agree on a joint task, the agents can provide their preferences for the alternative tasks, and the best alternative could be selected by majority. Previous works assumed that agents only provide their preferences for the alternatives. However, when selecting a joint task for teamwork, it is essential to consider not only the preferences of the agents, but also the probability of the agents being able to execute the task if it is selected. In this paper, we propose a novel model, the decIsion-MAking under Group commItmeNt modEl (IMAGINE), for computing the optimal decision for a team considering several parameters. Each agent provides: (1) the utility of each alternative for the team, (2) the associated cost for the agent by executing the alternative, and (3) the probability that the agent will be able to execute the alternative task. The IMAGINE gathers these data from the agents, as well as the requisite quorum for each alternative task, which is the minimum number of agents required to complete the task successfully. Given this information, the IMAGINE determines the optimal decision for the group. We evaluated the IMAGINE by comparing it to a baseline method that does not consider the quorum requirement. We show that the IMAGINE generally comes up with a better decision than the baseline method and that the higher the quorum, the better the decisions the IMAGINE makes are.

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“…Different from the traditional continuous control method, impulsive control has the advantages of low control cost, high control efficiency, and strong adaptability. Consequently, it is widely used in the research on leader-following consensus or group consensus of MASs [28][29][30]. Therefore, it is necessary to study the cluster-delay consensus of MASs via impulsive control [31].…”

Section: Introductionmentioning

confidence: 99%

Cluster-Delay Mean Square Consensus of Stochastic Multi-Agent Systems with Impulse Time Windows

Huan

Wang

Zhan

et al. 2021

Entropy

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This paper investigates the cluster-delay mean square consensus problem of a class of first-order nonlinear stochastic multi-agent systems with impulse time windows. Specifically, on the one hand, we have applied a discrete control mechanism (i.e., impulsive control) into the system instead of a continuous one, which has the advantages of low control cost, high convergence speed; on the other hand, we considered the existence of impulse time windows when modeling the system, that is, a single impulse appears randomly within a time window rather than an ideal fixed position. In addition, this paper also considers the influence of stochastic disturbances caused by fluctuations in the external environment. Then, based on algebraic graph theory and Lyapunov stability theory, some sufficiency conditions that the system must meet to reach the consensus state are given. Finally, we designed a simulation example to verify the feasibility of the obtained results.

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A survey of the consensus for multi-agent systems

Cited by 72 publications

References 163 publications

Cooperative Intersection Crossing Over 5G

Cooperative Intersection Crossing Over 5G

Decision-Making under Group Commitment

Cluster-Delay Mean Square Consensus of Stochastic Multi-Agent Systems with Impulse Time Windows

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