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Multi-agent adaptive consensus of networked systems on directed graphs

机译:有向图上网络系统的多智能体自适应共识

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This paper considers adaptive consensus problem on directed graphs of multi-agent systems with unknown control directions. The proposed consensus protocol assumes that each agent receives information about delayed values of state and control signals of respective neighbors. In case of unknown sign of the high-frequency gain of agent dynamics, the proposed algorithm employs Nussbaum-like switching function. The algorithm allows for a designer to select low gain or high gain consensus protocols. Assuming that the underlying graph is strongly connected, it is proved that all agent states converge toward the same value, and the inter-agent coupling parameters are convergent functions. Copyright (c) 2015John Wiley & Sons, Ltd.
机译:本文针对控制方向未知的多智能体系统的有向图,考虑了自适应共识问题。提出的共识协议假定每个代理都接收有关状态延迟值和相应邻居的控制信号的信息。在不知道代理动力学的高频增益的情况下,该算法采用类似于Nussbaum的切换功能。该算法允许设计人员选择低增益或高增益共识协议。假设基础图是强连通的,则证明所有主体状态朝着同一值收敛,并且主体间耦合参数是收敛函数。版权所有(c)2015 John Wiley&Sons,Ltd.

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