论文标题
具有随时间变化的参考信号的网络网络的强大动态平均共识
Robust Dynamic Average Consensus for a Network of Agents with Time-varying Reference Signals
论文作者
论文摘要
本文介绍了一组代理的连续动态平均共识（DAC）算法，以合作估计其随时间变化的参考信号的平均值。我们提出了共识算法，这些算法对加入和离开网络的代理人同时避免聊天现象，并保证零稳态共识误差。我们的算法是基于边缘的协议，其内部结构具有平滑的功能，以避免搅动效果。此外，每个代理只能执行本地计算，并且只能与其本地邻居进行通信。对于平衡且紧密连接的基础通信图，我们提供了收敛分析，以确定共识设计参数，以保证代理人对其平均值渐近地收敛到代理的时间变化参考信号的平均值。我们提供仿真结果，以验证提出的共识算法，并对文献中提出的算法进行性能比较。
This paper presents continuous dynamic average consensus (DAC) algorithms for a group of agents to estimate the average of their time-varying reference signals cooperatively. We propose consensus algorithms that are robust to agents joining and leaving the network, at the same time, avoid the chattering phenomena and guarantee zero steady-state consensus error. Our algorithms are edge-based protocols with smooth functions in their internal structure to avoid the chattering effect. Furthermore, each agent is only capable of performing local computations and can only communicate with its local neighbors. For a balanced and strongly connected underlying communication graph, we provide the convergence analysis to determine the consensus design parameters that guarantee the agents' estimate of their average to asymptotically converge to the average of the time-varying reference signals of the agents. We provide simulation results to validate the proposed consensus algorithms and to perform a performance comparison of the proposed algorithms to existing algorithms in the literature.
