The issue of stability and group consensus tracking is investigated for the discrete-time heterogeneous networked multi-agent systems with communication constraints(e.g.,time delays and data loss)in this paper.Firstly...The issue of stability and group consensus tracking is investigated for the discrete-time heterogeneous networked multi-agent systems with communication constraints(e.g.,time delays and data loss)in this paper.Firstly,the couple-group consensus tracking control is analyzed theoretically,the communication constraints are compensated by the prediction method,and the factor of leaders is introduced to make the system not lose generality.Secondly,the necessary and sufficient condition is given to ensure the stability of the system and achieve the couple-group consensus tracking control,and relax the topology constraint of in-degrees balance by cooperative-competitive interactions.In addition,the result of couple groups is extended to multiple groups based on the predictive control protocol.Numerical simulations with Matlab show that the proposed networked predictive control can effectively overcome the network constraints,the dynamic performance and control effect are better than the general control without the prediction.展开更多
When a mass of individual targets move closely, it is unpractical or unnecessary to localize and track every specific target in wireless sensor networks (WSN). However, they can be tracked as a whole by view of group ...When a mass of individual targets move closely, it is unpractical or unnecessary to localize and track every specific target in wireless sensor networks (WSN). However, they can be tracked as a whole by view of group target. In order to decrease the amount of energy spent on active sensing and communications, a flexible boundary detecting model for group target tracking in WSN is proposed, in which, the number of sensors involved in target tracking is adjustable. Unlike traditional one or multiple individual targets, the group target usually occupies a large area. To obtain global estimated position of group target, a divide-merge algorithm using convex hull is designed. In this algorithm, group target’s boundary is divided into several small pieces, and each one is enclosed by a convex hull which is constructed by a cluster of boundary sensors. Then, the information of these small convex hulls is sent back to a sink. Finally, big convex hull merged from these small ones is considered as the group target’s contour. According to our metric of precision evaluation, the simulation experiments confirm the efficiency and accuracy of this algorithm.展开更多
联合概率数据关联粒子滤波(joint probabilistic data association-particle filter,JPDA-PF)算法常被用来解决群目标跟踪中的数据关联和非线性滤波问题.针对算法的数据关联时间较长以及样本枯竭问题,本文阐述了一种利用模糊聚类和拟蒙...联合概率数据关联粒子滤波(joint probabilistic data association-particle filter,JPDA-PF)算法常被用来解决群目标跟踪中的数据关联和非线性滤波问题.针对算法的数据关联时间较长以及样本枯竭问题,本文阐述了一种利用模糊聚类和拟蒙特卡罗重采样的群目标跟踪算法.首先,在群演化网络模型的基础上,采用最大熵模糊聚类法来完成群内个体目标和量测之间的数据关联,利用模糊隶属度来构建互联概率矩阵.其次,在目标状态样本的重采样的过程中,利用随机化拟蒙特卡罗序列映射到拟复制样本的子空间上,提高样本的多样性,抑制样本枯竭的出现.仿真实验结果表明,与JPDA-PF算法相比,本文算法能有效估计群内目标状态和群结构,并具有更优的估计性能.展开更多
基金supported by Natural Science Foundation of Heilongjiang Province of China under Grant No.LH2022F033the National Natural Science Foundation of China under Grant Nos.61903104,61773144 and 12071102Heilongjiang Postdoctoral Scientific Research Developmental Fund under Grant Nos.LBHQ20099 and LBH-Q20168。
文摘The issue of stability and group consensus tracking is investigated for the discrete-time heterogeneous networked multi-agent systems with communication constraints(e.g.,time delays and data loss)in this paper.Firstly,the couple-group consensus tracking control is analyzed theoretically,the communication constraints are compensated by the prediction method,and the factor of leaders is introduced to make the system not lose generality.Secondly,the necessary and sufficient condition is given to ensure the stability of the system and achieve the couple-group consensus tracking control,and relax the topology constraint of in-degrees balance by cooperative-competitive interactions.In addition,the result of couple groups is extended to multiple groups based on the predictive control protocol.Numerical simulations with Matlab show that the proposed networked predictive control can effectively overcome the network constraints,the dynamic performance and control effect are better than the general control without the prediction.
文摘When a mass of individual targets move closely, it is unpractical or unnecessary to localize and track every specific target in wireless sensor networks (WSN). However, they can be tracked as a whole by view of group target. In order to decrease the amount of energy spent on active sensing and communications, a flexible boundary detecting model for group target tracking in WSN is proposed, in which, the number of sensors involved in target tracking is adjustable. Unlike traditional one or multiple individual targets, the group target usually occupies a large area. To obtain global estimated position of group target, a divide-merge algorithm using convex hull is designed. In this algorithm, group target’s boundary is divided into several small pieces, and each one is enclosed by a convex hull which is constructed by a cluster of boundary sensors. Then, the information of these small convex hulls is sent back to a sink. Finally, big convex hull merged from these small ones is considered as the group target’s contour. According to our metric of precision evaluation, the simulation experiments confirm the efficiency and accuracy of this algorithm.
文摘联合概率数据关联粒子滤波(joint probabilistic data association-particle filter,JPDA-PF)算法常被用来解决群目标跟踪中的数据关联和非线性滤波问题.针对算法的数据关联时间较长以及样本枯竭问题,本文阐述了一种利用模糊聚类和拟蒙特卡罗重采样的群目标跟踪算法.首先,在群演化网络模型的基础上,采用最大熵模糊聚类法来完成群内个体目标和量测之间的数据关联,利用模糊隶属度来构建互联概率矩阵.其次,在目标状态样本的重采样的过程中,利用随机化拟蒙特卡罗序列映射到拟复制样本的子空间上,提高样本的多样性,抑制样本枯竭的出现.仿真实验结果表明,与JPDA-PF算法相比,本文算法能有效估计群内目标状态和群结构,并具有更优的估计性能.
