Effect of network structure to the convergence rate of agents in multi-agent systems
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- 英文论文题名：Effect of network structure to the convergence rate of agents in multi-agent systems
- 论文作者：Shasha Feng ; Li Wang ; Shiwen Sun ; Chengyi Xia
- 英文论文作者：Shasha Feng ; Li Wang ; Shiwen Sun ; Chengyi Xia ; Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology ; Tianjin University of Technology
- 年：2017
- 作者机构：Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology;Tianjin University of Technology;
- 英文论文关键词：network structure ; convergence rate ; nodes number ; node position
- 会议召开时间：2017-07-26
- 会议录名称：第36届中国控制会议论文集（A）
- 英文会议录名称：Proceedings of the 36th Chinese Control Conference（A）
- 语种：英文
- 分类号：N941.4;O157.5
- 学会代码：KZLL
- 会议名称：第36届中国控制会议
- 会议地点：中国辽宁大连
- 主办单位：中国自动化学会控制理论专业委员会
- 学会名称：中国自动化学会控制理论专业委员会
- 页数：5
- 文件大小：545k
- 原文格式：D
- 会议级别：全国
摘要
In this paper, we probe into the influence of network structure on the convergence rate of agents in multi-agent systems, especially for the position and number of nodes of network on it. We discover some results of which kinds of networks are conductive to the faster convergence rate of agents in multi-agent systems. Firstly, if there is no ring in different networks where the number of nodes are same, then the network with fork nodes which are connected to the central position node is in favor of the faster convergence of agents; otherwise, the convergence rate of agents is quicker in the network without fork nodes.Secondly, it is inevitable for agents to converge more ane more slowly with the increasing of node number. One way to improve the convergence rate of agents is to enable the increased nodes to connect to the central position node. Finally, when both the position and the number of nodes of different networks are same, it can save communication cost to remove some edges in network under the condition that the convergence rate of agents is affected little. Therefore, we reveal that if the edges which do not connect to the central position directly are removed, then their impact on the convergence rate is little.
In this paper, we probe into the influence of network structure on the convergence rate of agents in multi-agent systems, especially for the position and number of nodes of network on it. We discover some results of which kinds of networks are conductive to the faster convergence rate of agents in multi-agent systems. Firstly, if there is no ring in different networks where the number of nodes are same, then the network with fork nodes which are connected to the central position node is in favor of the faster convergence of agents; otherwise, the convergence rate of agents is quicker in the network without fork nodes.Secondly, it is inevitable for agents to converge more ane more slowly with the increasing of node number. One way to improve the convergence rate of agents is to enable the increased nodes to connect to the central position node. Finally, when both the position and the number of nodes of different networks are same, it can save communication cost to remove some edges in network under the condition that the convergence rate of agents is affected little. Therefore, we reveal that if the edges which do not connect to the central position directly are removed, then their impact on the convergence rate is little.
In this paper, we probe into the influence of network structure on the convergence rate of agents in multi-agent systems, especially for the position and number of nodes of network on it. We discover some results of which kinds of networks are conductive to the faster convergence rate of agents in multi-agent systems. Firstly, if there is no ring in different networks where the number of nodes are same, then the network with fork nodes which are connected to the central position node is in favor of the faster convergence of agents; otherwise, the convergence rate of agents is quicker in the network without fork nodes.Secondly, it is inevitable for agents to converge more ane more slowly with the increasing of node number. One way to improve the convergence rate of agents is to enable the increased nodes to connect to the central position node. Finally, when both the position and the number of nodes of different networks are same, it can save communication cost to remove some edges in network under the condition that the convergence rate of agents is affected little. Therefore, we reveal that if the edges which do not connect to the central position directly are removed, then their impact on the convergence rate is little.
引文
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[14]Zhang HG,Feng T,Yang GH,Liang HJ,Distributed Cooperative Optimal Control for Multiagent Systems on Directed Graphs:An Inverse Optimal Approach,IEEE Trans.Cybern,45(7):1315-1326,2015.
[15]A.Jadbabaie,J.Lin,Coordination of groups of mobile agents using nearest neighbor rules,IEEE.Trans.Autom.,48(6):988-1001,2003.
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[2]Wang L,Chen ZQ,Liu ZX,Yuan ZZ,Finite time agreement protocol design of multi-agent systems with communication delays,Asian Journal of Control,11(3):281-286,2009.
[3]Chen MH,Wang L,Sun SW,Wang J,Xia CY,Evolution of cooperation in the spatial public goods game with adaptive reputation assortment,Physics Letters A,380(1-2):40-47,2016.
[4]Chen MH,Wang L,Wang J,Sun SW,Xia CY,Impact of individual response strategy on the spatial public goods game within mobile agents,Applied Mathematics and computation,251:192-202,2015.
[5]Zhang HG,Qin CB,Luo YH,Neural-network-based constrained optimal control scheme for discrete-time switched nonlinear system using dual heuristic programming,IEEE Trans.Autom.,11(3):839-849,2014.
[6]Zhang HG,Cui LL,Luo YH,Near-optimal control for nonzero-sum differential games of continuous-time nonlinear systems using single network,IEEE Trans.Cybern.,43(1):206-216,2013.
[7]Zhai SD,Modulus synchronization in a network of nonlinear systems with antagonistic interactions and switching topologies,Commun Nonlinear Sci Numer Simul,33:184-193,2016.
[8]Wang L,Sun SW,Xia CY,Finite-time stability of multi-agent system in disturbed environment,Nonlinear Dynamics,67(3):2009-2016,2012.
[9]Zhang HG,Zhang JL,Yang GH,Luo YH,Leader-Based Optimal Coordination Control for the Consensus Problem of Multiagent Differential Games via Fuzzy Adaptive Dynamic Programming,IEEE Trans.Fuzzy Syst.,23(1):152-163,2015.
[10]Cao YC,Yu WW,Ren W,Chen GR,An overview of recent progress in the study of distributed multi-agent coordination,IEEE Trans Ind Inform,9(1):427-438,2013.
[11]R.Olfati-Saber,R.M.Murray,Consensus Problems in networks of agents with switching topology and time delays,IEEE Trans.Autom.,49(9):1520-1533,2004.
[12]Y.Kim,Bisection Algorithm of Increasing Algebraic Connectivity by Adding an Edge,IEEE Trans.Autom.,55(1):170-174,2010.
[13]Li HQ,Liao XF,Lei XY,Huang TW,Zhu W,Second-Order Consensus Seeking in Multi-Agent Systems With Nonlinear Dynamics Over Random Switching Directed Networks,IEEE Trans.Circuits Syst.I,Reg.Papers,60(6):1595-1607,2013.
[14]Zhang HG,Feng T,Yang GH,Liang HJ,Distributed Cooperative Optimal Control for Multiagent Systems on Directed Graphs:An Inverse Optimal Approach,IEEE Trans.Cybern,45(7):1315-1326,2015.
[15]A.Jadbabaie,J.Lin,Coordination of groups of mobile agents using nearest neighbor rules,IEEE.Trans.Autom.,48(6):988-1001,2003.
[16]L.Xiao,S.Boyd,Fast linear iterations for distributed averaging,Systems&Control Letters,53(1):65-78,2004.
[17]R.Olfati-Saber,R.Murray,Consensus problems in networks of agents with switching topology and time-delays,IEEE Trans Autom Control 49(9):1520–2533,2004.