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

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

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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.

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