Convergence analysis of discrete-time consensus algorithm with both self and transmission delays
Convergence analysis of discrete-time consensus algorithm with both self and transmission delays
复制标题
具有自延迟和传输延迟的离散时间共识算法的收敛性分析
DOI：
10.1016/j.jfranklin.2016.05.001
复制
发表时间：
2016-07
期刊：
影响因子：
--
通讯作者：
Zhu Henghui
中科院分区：
文献类型：
--
作者：
Chen Yao;Li Fangfei;Hou Bo;Tan Shaolin;Zhu Henghui
多智能体系统（MAS）在真实的世界中无处不在，典型的例子包括传感器网络、群体机器人和鸟群。一致性是MAS最典型的动力学行为之一，它意味着群体的状态渐近地达到某个相同的值或轨迹。已有研究表明，离散时间MAS在不存在信息延迟的情况下能够实现一致性，但在传感器老化、执行器延迟或计算能力不足等情况下，可能出现自延迟现象。为了描述这种行为，本文引入了一个MAS模型，动态变化的拓扑结构，同时考虑自身和传输延迟。此外，这种模型的一个简单的共识准则提出。为了证明这一准则的正确性，我们提出了一种新的方法，该方法基于联合连通性和序列连通性之间的内在联系，但不依赖于广泛使用的Wolfowitz定理，即随机矩阵无穷乘积的收敛性.
Multi-agent systems (MAS) are ubiquitous in the real world, typical examples include sensor networks, group robots, and birds flock. Consensus is one of the most typical dynamical behaviors of MAS which implies the states of a group reach some identical value or trajectory asymptotically. It has been widely demonstrated that discrete-time MAS can realize consensus when there does not exist information delay from any node to itself, however, the phenomenon of self delay is possible to occur in cases like sensor aging, actuator delay, or computation incapacity. To characterize such a behavior, this paper introduces an MAS model with dynamically changing topologies by considering both self and transmission delays. Moreover, a simple consensus criterion for such a model is proposed. To prove the correctness of such a criterion, we propose a novel method which is based on the intrinsic relationship between joint and sequential connectivity, it should be noted that such a method does not rely on the widely used Wolfowitz׳s theorem for convergence of infinite products of stochastic matrices.
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DOI：
10.1016/j.sysconle.2011.04.009
发表时间：
2011-07
期刊：
Syst. Control. Lett.
影响因子：
--
作者：
Yao Chen;Jinhu Lu;F. Han;Xinghuo Yu
通讯作者：
Yao Chen;Jinhu Lu;F. Han;Xinghuo Yu
具有传输非线性的离散时间多智能体系统的共识
影响因子：
6.4
作者：
Chen, Yao;Lu, Jinhu;Lin, Zongli
通讯作者：
Lin, Zongli
影响因子：
6.8
作者：
Jadbabaie, A;Lin, J;Morse, AS
通讯作者：
Morse, AS
影响因子：
6.8
作者：
Ren, W;Beard, RW
通讯作者：
Beard, RW
影响因子：
3.9
作者：
G. Wen;Z. Duan;Wenwu Yu;Guanrong Chen
通讯作者：
G. Wen;Z. Duan;Wenwu Yu;Guanrong Chen