Distributed Average Tracking in Multi-Agent Coordination: Extensions and Experiments
Distributed Average Tracking in Multi-Agent Coordination: Extensions and Experiments
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DOI：
10.1109/jsyst.2017.2685465
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发表时间：
2018-09
影响因子：
4.4
通讯作者：
Muhammad Saim;S. Ghapani;W. Ren;K. Munawar;U. Al-Saggaf
中科院分区：
文献类型：
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作者：
Muhammad Saim;S. Ghapani;W. Ren;K. Munawar;U. Al-Saggaf
本文解决了一组智能体的分布式平均跟踪（DAT）问题，以在与邻居和无向图的本地交互下跟踪多个时变参考信号的平均值，每个参考信号仅可供一个智能体使用。我们考虑三种情况：1）算法设计中具有一系列积分器的单积分器动力学的 DAT； 2) 针对单积分器动力学的具有群体行为的 DAT； 3）具有群行为的 DAT，用于双积分器动力学。首先，针对单积分器动力学提出了一种具有两个积分器链的连续分布式算法，其中每个智能体除了其绝对位置、局部相对位置、参考信号和参考速度之外，还需要通过通信获得自己及其邻居的滤波器输出。引入的算法可以处理各种参考速度之间具有稳定偏差的参考信号。然后，提出了两种基于群的 DAT 算法，分别用于单积分器和双积分器动力学。在第一个基于群的单积分器动力学算法中，每个代理需要测量其自身与其邻居之间的相对位置，而在第二个基于群的双积分器动力学算法中，也需要相对速度信息。在这两种情况下，都可以通过本地传感来获取信息。如果可以实现正确的初始化约束，则代理中心将跟踪参考信号的平均值，并且代理将保持连接并避免代理间冲突。还提出了数值模拟来说明理论结果。最后，本文提出的算法在多机器人平台上进行了实验实现和验证。
This paper addresses the distributed average tracking (DAT) problem for a group of agents to track the average of multiple time-varying reference signals, each of which is available to only one agent, under local interaction with neighbors and an undirected graph. We consider three cases: 1) DAT for single-integrator dynamics with a chain of integrators in algorithm design; 2) DAT with swarm behavior for single-integrator dynamics; and 3) DAT with swarm behavior for double-integrator dynamics. First, a continuous distributed algorithm with a chain of two integrators is proposed for single-integrator dynamics, where each agent needs its own and its neighbors’ filter outputs obtained through communication besides its absolute position, local relative positions, reference signal, and reference velocity. The introduced algorithm can deal with a wide class of reference signals with steady deviations among reference velocities. Then, two swarm-based DAT algorithms for, respectively, single- and double-integrator dynamics are presented. In the first swarm-based algorithm for single-integrator dynamics, each agent needs to measure the relative positions between itself and its neighbors, while in the second swarm-based algorithm for double-integrator dynamics, relative velocity information is required too. In both cases, the information can be obtained through local sensing. If correct initialization constraints can be achieved, the center of the agents will track the average of the reference signals and the agents will maintain connectivity and avoid interagent collision. Numerical simulations are also presented to illustrate the theoretical results. Finally, the algorithms presented in this paper are experimentally implemented and validated on a multirobot platform.