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 .
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