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Stability and convergence analysis of multi-agent consensus with information reuse

机译:具有信息重用的多主体共识的稳定性和收敛性分析

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摘要

In this article, we study multi-agent consensus algorithms with information reuse by intentionally introducing the outdated state information into the traditional consensus algorithms. In the continuous-time case, we first show that the outdated state information combined with the current state information does not necessarily jeopardise the stability of a single system, but may improve the convergence speed without increasing the maximal control effort. Then this idea is extended from the single-agent case to the multi-agent case. When the directed communication graph is fixed, the corresponding Laplacian matrix and the outdated state information satisfy certain conditions, we show that the consensus algorithm with both the current and outdated states can achieve a faster convergence speed than the standard one. We also consider the case of a switching directed communication graph and derive corresponding conditions. In the discrete-time case, we propose a discrete-time consensus algorithm with both the current and outdated states under an undirected fixed communication graph. We then derive conditions on the communication graph, the sampling period and the outdated state information such that the proposed algorithm can achieve a faster convergence speed than that using the standard one. In both the continuous-time and discrete-time settings, we show that the maximum control efforts for the proposed consensus algorithms are identical to those for the standard ones. Several simulation examples are presented as a proof of concept.
机译:在本文中,我们有意将过时的状态信息引入传统的共识算法中,研究了具有信息重用的多主体共识算法。在连续时间情况下,我们首先表明,过时的状态信息与当前状态信息相结合并不一定会危害单个系统的稳定性,但可以提高收敛速度而不会增加最大的控制量。然后,这个想法从单代理案例扩展到多代理案例。当有向通信图固定时,相应的拉普拉斯矩阵和过时的状态信息满足特定条件,我们表明,具有当前状态和过时状态的共识算法可以实现比标准方法更快的收敛速度。我们还考虑了交换定向通信图的情况,并推导了相应的条件。在离散时间情况下,我们提出了一种在无向固定通信图下具有当前状态和过时状态的离散时间共识算法。然后,我们在通信图,采样周期和过时的状态信息上得出条件,从而使所提出的算法可以比使用标准算法实现更快的收敛速度。在连续时间和离散时间设置中,我们都表明,所提出的共识算法的最大控制量与标准算法的最大控制量相同。给出了几个仿真示例作为概念验证。

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