Group consensus control for heterogeneous multi-agent systems with fixed and switching topologies

Wen, Guoguang; Huang, Jun; Wang, Chun Yan; Chen, Zhi; Peng, Zhaoxia

doi:10.1080/00207179.2015.1072876

Cited by 89 publications

(59 citation statements)

References 37 publications

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“…In the related works [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24], the cooperative and competitive relationship between the Complexity 3 agents and is described as − and + , respectively. In [25,26], they also are presented by the coupling weight between these two agents.…”

Section: Resultsmentioning

confidence: 99%

“…It is worth noting that there is a virtual velocity estimation in the dynamics of the first-order agents for the convenience of analysis in [15,[21][22][23]. In fact, this situation is so ideal that it cannot meet the requirement in applications.…”

Section: Remarkmentioning

confidence: 99%

“…In [19][20][21], group consensus problems for different kinds of heterogeneous systems have been investigated, such as the discrete-time complex systems, the systems modeled 2 Complexity by second-order, and Euler-Lagrange networks. In [22,23], the authors studied the group consensus for the cooperative and heterogeneous networks with and without input time delays, respectively. In [24], group synchronization for linear and nonlinear heterogeneous systems was discussed via Lyapunov theory.…”

Section: Introductionmentioning

confidence: 99%

“…Our contributions are mainly listed as below: firstly, two novel delayed group consensus protocols are proposed, which is modeled by the agents' competitive relationship. The innovation is mainly embodied in the following two aspects: on the one hand, the related works [10][11][12][13][14][15][16][17][18][19][20][21][22][23][24] are based on the cooperative complex systems. On the other hand, there is a special case in the works [15,[21][22][23]; that is, the dynamics of the first-order agents are added with a virtual velocity estimation in order to make theoretical analysis more convenient.…”

Section: Introductionmentioning

confidence: 99%

“…Hence, we relax it in our protocol. Secondly, we also relax the following two preconditions in [15,[20][21][22][23][24]: in-degree balance and the geometric multiplicity of zero eigenvalues of the Laplacian matrix associated with the adjacency matrix are at least two. They limit the topology of the system and the information interaction between the agents.…”

Section: Introductionmentioning

confidence: 99%

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Heterogeneous and Competitive Multiagent Networks: Couple-Group Consensus with Communication or Input Time Delays

2017

Complexity

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This paper discusses the couple-group consensus problems for a class of heterogeneous multiagent networks including the following two cases: with communication and input time delays, respectively. Different from the related cooperative networks, two novel delayed group consensus protocols are designed based on the competitive relationship between the agents. Furthermore, we absolutely relax the in-degree balance and other restrictive preconditions which existed in the relevant works. Some sufficient algebraic criteria for the achievement of couple-group consensus and the upper bound of the input time delays are technically obtained via the frequency domain method and matrix theory, respectively. The results show that the achievement of the couple-group consensus depends on the second-order agents' in-degree and the control parameters of the systems, whereas it is independent of the communication time delays. Meanwhile, the upper bound of the input time delay is determined by the control parameters and the in-degree of the first-order agents. Finally, the validity of the proposed results is verified by several simulated examples.

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Section: Resultsmentioning

confidence: 99%

Section: Remarkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Heterogeneous and Competitive Multiagent Networks: Couple-Group Consensus with Communication or Input Time Delays

2017

Complexity

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Scaled consensus for MASs with compound noises over Markovian switched topologies

Liang

Liu

et al. 2023

Asian Journal of Control

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This article aims to address the stochastic scaled consensus issue in almost surely and mean square sense of stochastic multiagent systems (SMASs) with compound noises in a Markovian switching setting. At first, based on stochastic approximation technique and nearest‐neighbor interaction rules, the stochastic scaled consensus controller is built for SMASs in presence of multiplicative and additive noise by designing a time‐varying gain. Meanwhile, some consensus criterions of SMASs are addressed if the union of the graph and time‐varying gain fulfill some mild requirements. Furthermore, the scaled consensus means that the agents' state variables tend to a prescribed proportion rather than the common value, so this behavior can be seen as non‐convergent behavior. The difference with most of excellent literatures is that the coexistence of noncooperative behavior and multiplicative noise generates that it is not easy to transform the multiplicative noise term into the form of an error equation, which means that the Lyapunov methods cannot be directly utilized in our article. To cope with this, we first demonstrate the boundedness for each agent's state, and hence the convergence can be achieved. Finally, in order to reveal the efficiency of our proposed protocol, the corresponding example is given in the simulation part.

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Sampled‐data based resilient consensus of heterogeneous multiagent systems

Zhu

Zhou

Zheng

et al. 2020

Intl J Robust & Nonlinear

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This article studies consensus of a group of heterogeneous agents with first-order and second-order integrator dynamics in presence of malicious agents. We employ the algorithm where each normal agent ignores large and small relative state values of its neighbors to mitigate the effects of malicious agents. Assuming that the maximum number of malicious agents in the neighborhood of each agent is known, sufficient topological condition is obtained to guarantee resilient consensus in directed networks. The result is further extended to heterogeneous multiagent systems with bounded communication delays. Moreover, impulsive control strategy is introduced in the update schemes and sufficient condition in terms of graph robustness is provided for resilient consensus. Numerical examples are provided to illustrate the effectiveness of the theoretical results. K E Y W O R D S communication delays, heterogeneous multiagent systems, resilient consensus, sampled-data 1 INTRODUCTION Considerable attention has been paid to coordination of multiagent systems in the past decades because of its wide application in many fields, such as distributed computation, mobile robots formation, and intelligent transportation systems. Consensus problem, which is a fundamental problem in multiagent systems, aims at making a group of locally interacting agents reach an agreement upon some quantities of interest. So far, lots of work has been done under different contexts, such as communication delays, 1 noise, 2 quantization, 3 states constraints, 4 and fast consensus. 5 In most of the existing literature on the consensus problem, the agents are cooperative to achieve the global goal. However, some agents may become noncooperative or even malicious when the network is suffering malicious attack or platform-level failures, which will lead to degradation of system performance and even failure of the global goal. Therefore, it is of great importance to consider how to improve the algorithms to avoid system performance being influenced by such compromised agents. Resilient consensus, as a special case of consensus, has long been studied in computer science. A class of algorithms where each normal agent disregards the most deviated agents in the updates has been extensively used for resilient consensus and is often called the mean subsequence reduced (MSR) algorithms. 6 However, this strategy had been studied mostly under complete graphs. In Reference 7, a new concept in graph theory, termed r-robustness, was introduced to study resilient consensus in noncomplete networks. Afterward, a lot of excellent work emerged in discrete-time setting by employing the concept of network robustness and MSR-type algorithms. In References 8 and 9, resilient conditions were obtained for second-order multiagent systems under DP-MSR algorithm, which took an adapted form of the MSR-type algorithms for second-order multiagent systems. In Reference 10, SW-MSR algorithm, which extended MSR-type algorithm by introducing a sliding window, was introduced for multiagent sys...

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Group consensus control for heterogeneous multi-agent systems with fixed and switching topologies

Abstract: International audienc

Cited by 89 publications

References 37 publications

Heterogeneous and Competitive Multiagent Networks: Couple-Group Consensus with Communication or Input Time Delays

Heterogeneous and Competitive Multiagent Networks: Couple-Group Consensus with Communication or Input Time Delays

Scaled consensus for MASs with compound noises over Markovian switched topologies

Sampled‐data based resilient consensus of heterogeneous multiagent systems

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