Second-order consensus of hybrid multi-agent systems

Zheng, Yufan; Zhao, Qi; Ma, Jingying; Wang, Long

doi:10.1016/j.sysconle.2019.01.009

Cited by 137 publications

(48 citation statements)

References 35 publications

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“…Sufficient and necessary conditions for consensus are characterized. The results are further extended in [11] to second-order consensus of hybrid multi-agent systems. In [12], consensus analysis is built upon a game-theoretic approach to regulating the interaction between discrete-time and continuous-time agents.…”

Section: Introductionmentioning

confidence: 99%

Consensus of Hybrid Multi-Agent Systems With Malicious Nodes

Shang

2020

IEEE Trans. Circuits Syst. II

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This brief investigates resilient consensus problems of hybrid multi-agent systems containing both continuous-time dynamical agents and discrete-time dynamical agents. A hybrid censoring strategy is developed to reach resilient consensus for cooperative agents in the directed networks in which some Byzantine agents are present. The number, location, and dynamics of Byzantine agents are assumed to be unavailable to the cooperative agents. Sufficient conditions based on network robustness are established when the number of Byzantine agents is locally bounded. They are further extended to cope with resilient scaled hybrid consensus where dictated ratios instead of a common value can be reached. Numerical examples are presented to illustrate the theoretical results.

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Section: Introductionmentioning

confidence: 99%

Consensus of Hybrid Multi-Agent Systems With Malicious Nodes

Shang

2020

IEEE Trans. Circuits Syst. II

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“…It is the necessary prerequisite for the correctness of other collective behaviors in MANs, such as flocking, formation, and distributed optimization. For this reason, a number of papers devoted to designing consensus algorithms in various scenarios have appeared during the past decade (e.g., [1]- [5]).…”

Section: Introductionmentioning

confidence: 99%

“…The initial state of agents are selected randomly as x(0) = col(15,8,4, −1, −7, −12). For simplicity, the adjacency matrix is selected as a binary matrix, whose element is either 1 or 0, and the coupling weight matrix = [φ ij ] is chosen as appropriately choosing sampling time T = 0.5s, one can check that T φ ij a ij < 1, ∀j ∈ N i , which meets Prerequisite 11.Suppose that the links(1,3),(1,6),(2,4),(3,2),(3,5),(5,1) are compromised by deception attacks. Let us select the following false information x a j (k):…”

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confidence: 99%

Event-Triggered Resilient Consensus for Multi-Agent Networks Under Deception Attacks

Zheng

et al. 2020

IEEE Access

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In this paper, a novel distributed algorithm derived from the event-triggered strategy is proposed for achieving resilient consensus of multi-agent networks (MANs) under deception attacks. These malicious deception attacks are intended to interfere with the communication channel causing periods in time at which the sending information among nodes is modified. In particular, we develop an event-triggered update rule which can mitigate the influence of the attackers and at the same time reduce the computing and communication consumption. Each node chooses the instances to update its state information by checking whether its neighbor set meets a given cardinality-dependent function or not. With specified prerequisite on the coupling weights and the sampling period, the consensus achievement of the MANs is independent of the deception attacks, but strictly depends on the robustness of the interconnection topology. Simulation examples are finally given to illustrate the efficacy of the theoretical results. INDEX TERMS Multi-agent networks, resilient consensus, event-triggered, deception attack.

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“…Applications of such systems arise in various fields including cyber‐physical systems, multicell wireless data networks, power grid, among others. Along with this fact, consensus problems of hybrid multiagent systems, in which continuous‐time dynamic agents (CT‐agents) and discrete‐time agents (DT‐agents) coexist, were explored in the works of Zheng et al Inspired by Zheng et al, this paper intends to propose a new consensus protocol for hybrid multiagent systems, which contain two groups of agents: a group of CT‐agents and a group of DT‐agents. Different from the works of Zheng et al, a game‐theoretic model is adopted in this paper to describe the interactions among the agents in distinct groups.…”

Section: Introductionmentioning

confidence: 99%

Consensus analysis of hybrid multiagent systems: A game‐theoretic approach

Zheng

et al. 2019

Intl J Robust & Nonlinear

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Summary This paper considers a consensus problem for hybrid multiagent systems, which comprise two groups of agents: a group of continuous‐time dynamic agents and a group of discrete‐time dynamic agents. Firstly, a game‐theoretic approach is adopted to model the interactions between the two groups of agents. To achieve consensus for the considered hybrid multiagent systems, the cost functions are designed. Moreover, it is shown that the designed game admits a unique Nash equilibrium. Secondly, sufficient/necessary conditions of solving consensus are established. Thirdly, we find that the convergence speed of the system depends on the game. By the mechanism design of the game, the convergence speed is increased. Finally, simulation examples are given to validate the effectiveness of the theoretical results.

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Second-order consensus of hybrid multi-agent systems

Cited by 137 publications

References 35 publications

Consensus of Hybrid Multi-Agent Systems With Malicious Nodes

Consensus of Hybrid Multi-Agent Systems With Malicious Nodes

Event-Triggered Resilient Consensus for Multi-Agent Networks Under Deception Attacks

Consensus analysis of hybrid multiagent systems: A game‐theoretic approach

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