【摘要】 为解决复杂环境中多智能体系统实现一致过程中存在的时滞问题,并提升系统一致收敛速度,提出了带有延时的基于二级网络的多智能体一致性控制和一致性跟踪算法。通过建立单积分动力模型,运用李雅普诺夫定理证明了该控制算法可使系统在存在由通信带宽、信号传输速度、通信范围等通信条件受限导致的通信延时和智能体信息处理过程导致的输入延时的情况下仍实现一致,二级网络通信拓扑使得系统一致收敛速度得以提升,最后在此基础上研究了编队控制算法。实验仿真结果表明该算法可使系统在存在延时的环境中以更快的速度实现一致,进而完成编队控制。更多还原

【Abstract】 A consensus control and a consensus tracking algorithm for multi-agent system based on twohop relay network with diverse time delays were proposed to solve the problem of time-delay and improve the convergence speed during the process that the system reaches consensus. By building the single-integrator dynamic model, the proposed algorithm were proved to verify that it could make the system achieve convergence in the case of communication delay caused by limited communication conditions like communication bandwidth, signal transmission speed, communication range, and input delay due to the signal processing by means of Lyapunov theorem and the convergence speed has been improved owing to two-hop relay network. Then, the related consensus formation control algorithm were presented. Some simulation results are provided to validate the effectiveness of the proposed algorithms.更多还原