面向分布式融合估计的快速一致性算法

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英文篇名：Fast Consensus Algorithm for Distributed Fusion Estimation 作者：石晓航 ; 梁青阳 ; 张庆杰 ; 李强 ; 樊超宇 英文作者：SHI Xiao-hang;LIANG Qing-yang;ZHANG Qing-jie;LI Qiang;FAN Chao-yu;Aviation University of Air Force;Changchun University of Technology; 关键词：传感器网络 ; 信息融合 ; 分布式 ; 一致性 ; 快速收敛 英文关键词：sensor network;;information fusion;;distributed;;consensus;;fast convergence 中文刊名：DGKQ 英文刊名：Electronics Optics & Control 机构：空军航空大学;长春工业大学; 出版日期：2014-05-30 14:06 出版单位：电光与控制 年：2014 期：v.21;No.192 基金：国家自然科学基金(61203355);; 吉林省科技发展计划资助项目(20130522108JH) 语种：中文; 页：DGKQ201406008 页数：5 CN：06 ISSN：41-1227/TN 分类号：42-46

摘要

针对分布式多传感器网络信息融合估计问题,提出一种快速一致性算法。首先,对图论知识、多智能体平均一致性算法以及加权矩阵进行描述;其次,利用LMS原理以及本地节点与邻居节点的估计误差定义代价函数,并利用其对加权矩阵进行更新,得到快速一致性算法,同时简要介绍了参数选取问题;最后,对常用加权矩阵进行仿真实验。结果表明,快速一致性算法能够提高一致性的收敛速度,在传感器网络连通度较低时效果明显。
        To the information fusion estimation in distributed multi-sensor network,a consensus algorithm that can improve the convergence speed is proposed.Firstly,the graph theory,the conventional average consensus algorithm and the weighting matrices are introduced.Then,the cost function is defined by the LMS principle and the estimation error between the local node and its neighbor nodes,and the weighting matrices are updated by the cost function.Thus the fast consensus algorithm can be obtained.The parameter selection is also introduced briefly.Simulation was carried out using several common weighting matrices.The results show that the fast consensus algorithm can improve the convergence speed,especially for the sensor network with low connectivity.

引文

[1]何友,王国宏,陆大纟金,等.多传感器信息融合及应用[M].北京:电子工业出版社,2007.HE Y,WANG G H,LU D J,et al.Multisensor information fusion with applications[M].Beijing:Electronics Industry Press,2007.
    [2]XIAO L,BOYD S,LALL S.A scheme for robust distributed sensor fusion based on average consensus[C]//Information Processing in Sensor Networks(IPSN),2005:63-70.
    [3]张庆杰,朱华勇,沈林成.多智能体一致性理论研究进展[C]//2010中国制导、导航与控制学术会议(CG NCC2010),2010:40-46.ZHANG Q J,ZHU H Y,SHEN L C.A survey of consensus theory in multi-agent system[C]//CGNCC 2010,2010:40-46.
    [4]SPANOS D P,OLFATI-SABER R,MURRAY R M.Approximate distributed Kalman filtering in sensor networks with quantifiable performance[C]//The Fourth International Symposium on Information Processing in Sensor Networks,2005:133-139.
    [5]OLFATI-SABER R.Distributed Kalman filtering for sensor networks[C]//The 46th IEEE Conference on Decision and Control,2007:5492-5498.
    [6]TALEBI M S,KEFAYATI M,KHALAJ B H,et al.Adaptive consensus averaging for information fusion over sensor network[C]//Proceedings of the IEEE International Conference on Mobile Adhoc and Sensor Systems,2006:562-565.
    [7]OLFATI-SABER R,MURRAY R M.Consensus problems in networks of agents with switching topology and timedelays[J].IEEE Transactions on Automatic Control,2004,49(9):1520-1533.
    [8]刘成林,田玉平.具有时延的多个体系统的一致性问题综述[J].控制与决策,2009,24(11):1601-1608,1614.LIU C L,TIAN Y P.Survey on consensus problem of multi-agent systems with time delays[J].Control and Decision,2009,24(11):1601-1608,1614.
    [9]ZHOU J,WANG Q.Convergence speed in distributed consensus over dynamically switching random networks[J].Automatica,2009,45(6):1455-1461.
    [10]王林.多无人机协同目标跟踪问题建模与优化技术研究[D].长沙:国防科学技术大学,2011.WANG L.Modeling and optimization for multi-UAV cooperative target tracking[D].Changsha:National University of Defense Technology,2011.