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Controlling complex network dynamics using sparse measurements and actuation: Graph-theoretic perspective.

机译：使用稀疏测量和驱动来控制复杂的网络动力学：图论的角度。

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摘要

This thesis studies the control and estimation of hardwired network processes with sparse actuation and sensing from a topological perspective. This topological characterization is achieved in the context of several evocative linear models for network dynamics. For these models, formal relationships between the network's graph topology and properties of the network's actuated/measured dynamics have been developed.;One thrust of the research has been on estimation and identification of linear network synchronization processes. We provide graph-theoretic characterizations of 1) the mode estimation performance, as indicated by the Cramer-Rao Bound; and 2) structural-change detection, which is phrased as a Maximum A Posteriori probability detection problem. Our analysis indicates linkages between the network topology, the sensor locations, and the estimation/detection performance, which provide insight into optimal sensor placement. Further, we present a case study on fast fault location in power transmission networks using synchrophasor measurements.;A second thrust has been on feedback control of linear network processes with essentially-nonnegative state matrices, which encompass spread and synchronization processes. First, the input-output behavior of a network dynamics in which only one network component/channel can be actuated and another (in general remote) network component can be measured is studied. In this single-input single-output case, we characterize the infinite- and finite- zero structure in terms of the network's graph, and the actuation/measurement location. Using these results, we provide graph-theoretic conditions for determining whether the system is non-minimum phase, i.e. there are input-output zeros in the right-half plane, which provide insight into feedback-control performance and robustness. We also consider decentralized control of the network dynamics. In this case, we provide a constructive design of optimal static decentralized feedback, when control capabilities are available at a subset of the network's channels, and give graph-theoretic insights into the design.
机译：本文从拓扑的角度研究了稀疏驱动和感知的硬连线网络过程的控制和估计。这种拓扑特征是在网络动力学的多个线性模型的背景下实现的。对于这些模型，已经开发了网络的图拓扑与网络的致动/测量动力学特性之间的形式关系。研究的重点之一是线性网络同步过程的估计和识别。我们提供图论特征：1）模式估计性能，如Cramer-Rao Bound所示； 2）结构变化检测，被表述为最大后验概率检测问题。我们的分析表明，网络拓扑，传感器位置和估计/检测性能之间存在联系，从而可以洞悉最佳传感器的位置。此外，我们还提供了一个使用同步相量测量进行输电网络快速故障定位的案例研究。第二个重点是对具有本质为负状态矩阵的线性网络过程的反馈控制，该过程包括扩展过程和同步过程。首先，研究了网络动力学的输入输出行为，其中只有一个网络组件/通道可以被激活，而另一个（通常是远程）网络组件可以被测量。在这种单输入单输出的情况下，我们根据网络的图以及驱动/测量位置来表征无限零和有限零结构。使用这些结果，我们提供了图形理论条件来确定系统是否为非最小相位，即右半平面中存在输入输出零，从而可以深入了解反馈控制性能和鲁棒性。我们还考虑网络动态的分散控制。在这种情况下，当控制能力在网络通道的一个子集上可用时，我们将提供最佳静态静态分散反馈的结构设计，并对设计提供图形理论的见解。

著录项

  • 作者

    Abad Torres, Jackeline.;

  • 作者单位

    Washington State University.;

  • 授予单位 Washington State University.;
  • 学科 Electrical engineering.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 287 p.
  • 总页数 287
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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