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arXiv 1909.08008cs.MA
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线性异构多智能体系统主动领导者的分布式领导者跟踪

Distributed Leader Following of an Active Leader for Linear Heterogeneous Multi-Agent Systems

Yi-Fan Chung, Solmaz S. Kia

摘要:

本文研究了一类在有向无环图上相互作用的异质线性时不变(LTI)跟随者的领导-跟随问题。在特定的采样时间内,只有一部分followers可以访问leader的状态。产生其采样状态的领导者的动态对于跟随者是未知的。对于交互拓扑中的领导者是一个全球性的水槽图中,我们提出了一个分布式算法,允许追随者到达采样状态的领导者的时间,下一个样本到达。我们的算法是一个实用的解决方案的领导者以下的问题时,有没有信息可用的状态的领导者,除了其在采样时间的瞬时值。我们的算法还允许追随者跟踪采样状态的领导者与本地选择的偏移量,可以随时间变化。当追随者是移动代理的状态或其状态的一部分是他们的位置向量时,偏移机制可以用来使追随者形成一个关于领导者的采样状态的跨国不变编队。我们证明了控制输入的追随者,使他们从一个采样状态到下一个是最小的能量。我们还表明,在同质的追随者的情况下,在第一次采样后,所有的追随者的状态和输入彼此同步。数值例子验证了我们的结果。

英文摘要:

This paper considers a leader-following problem for a group of heterogeneous linear time invariant (LTI) followers that are interacting over a directed acyclic graph. Only a subset of the followers has access to the state of the leader in specific sampling times. The dynamics of the leader that generates its sampled states is unknown to the followers. For interaction topologies in which the leader is a global sink in the graph, we propose a distributed algorithm that allows the followers to arrive at the sampled state of the leader by the time the next sample arrives. Our algorithm is a practical solution for a leader-following problem when there is no information available about the state of the leader except its instantaneous value at the sampling times. Our algorithm also allows the followers to track the sampled state of the leader with a locally chosen offset that can be time-varying. When the followers are mobile agents whose state or part of their state is their position vector, the offset mechanism can be used to enable the followers to form a transnational invariant formation about the sampled state of the leader. We prove that the control input of the followers to take them from one sampled state to the next one is minimum energy. We also show in case of the homogeneous followers, after the first sampling epoch the states and inputs of all the followers are synchronized with each other. Numerical examples demonstrate our results.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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