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An Iterative Learning Control Approach for Synchronization of Multi-agent Systems under Iteration-varying Graph

机译:一种迭代学习控制方法,用于在迭代 - 变化下的多算法系统同步

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In this work, an iterative learning control (ILC) strategy is applied to synchronize the outputs from a group of homogeneous agents under iteration-varying communication topology. First, we show that the ILC strategy works for fixed strongly connected graph, which lays out the analysis framework for the rest developments. Next, the result is extended to iteration-varying topology, where the graph is strongly connected in each iteration. Then, the result is further generalized to uniformly strongly connected graph along the iteration domain. Matrix norm properties together with contraction mapping based analysis are utilized to prove the results. Finally, a numerical example is presented to verify the obtained results.
机译:在这项工作中,应用迭代学习控制(ILC)策略以在迭代不同通信拓扑下将输出与一组均匀代理同步。首先,我们表明ILC策略适用于固定的强烈连接的图表,这为REST开发提供了分析框架。接下来,结果扩展到迭代变化拓扑,其中图表在每次迭代中强烈连接。然后,结果进一步推广以沿迭代域均匀地连接的图。基于基于收缩映射的矩阵规范属性用于证明结果。最后,提出了一个数值例子以验证所获得的结果。

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