The paper presents new results on asymptotic consensus for continuous time nonautonomous nonlinear networks under almost-periodic interactions. We introduce such consensus algorithms in order to estimate the average of a measured field, despite the presence of limited agents' interaction (herein represented by almost periodic connectivity). To this end, a suitable notion of integral connectivity is exploited, frozen in state variables, and of simple verification, thanks to ergodicity of the underlying agents' spatial dynamics. In the considered setup, consensus variables are different than those affecting network's connectivity unlike most of the existing literature on asymptotic agreement. The application of the proposed results is illustrated considering two representative examples in the scenario of autonomous sampling by mobile sensor agents.

中文翻译：

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近周期连通性时变非线性网络场平均的渐近一致性


该论文提出了近周期相互作用下连续时间非自治非线性网络渐近一致性的新结果。我们引入这种共识算法是为了估计测量场的平均值，尽管存在有限的代理交互（这里由几乎周期性的连接表示）。为此，由于底层智能体空间动力学的遍历性，利用了适当的积分连接概念，冻结在状态变量中，并进行简单验证。在所考虑的设置中，共识变量与影响网络连接的变量不同，这与大多数关于渐近协议的现有文献不同。考虑移动传感器代理自主采样场景中的两个代表性示例，说明了所提出的结果的应用。