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Hierarchical nearly cyclic pursuit for consensus in large-scale multi-agent systems

机译:大规模多主体系统中对共识的分层近乎周期性的追求

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The authors solve the rendezvous problem of multi-agent systems using nearly cyclic pursuit (NCP) and hierarchical NCP (HNCP). First, the control law designed under the NCP strategy enables agents to converge at a point dictated by a beacon. Second, they elevate the NCP strategy into the generalised L-layer HNCP, so that a large-scale system under the NCP can be divided into small groups in the hierarchical structure, leading to increasing its convergence rate compared with the original NCP. Finally, they prove that the HNCP strategy with fewer communication links achieves the same convergence rate as the hierarchical cyclic pursuit. They provide simulation results to demonstrate their method.
机译:作者使用近循环追踪(NCP)和分层NCP(HNCP)解决了多智能体系统的集合点问题。首先,在NCP策略下设计的控制法使代理可以在信标指示的位置收敛。其次,他们将NCP策略提升为广义的L层HNCP,以便将NCP下的大型系统按层次结构划分为小类,从而与原始NCP相比提高了收敛速度。最后,他们证明了具有较少通信链路的HNCP策略可达到与分层循环追踪相同的收敛速度。他们提供了仿真结果来证明他们的方法。

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