State Estimation Model Reduction Through the Manifold Boundary Approximation Method
State Estimation Model Reduction Through the Manifold Boundary Approximation Method
复制标题
通过流形边界逼近法简化状态估计模型
DOI：
10.1109/tpwrs.2021.3091547
复制
发表时间：
2022
影响因子：
6.6
通讯作者：
Stankovic, Aleksandar
中科院分区：
文献类型：
--
作者：
Svenda, Vanja;Transtrum, Mark;Francis, Benjamin;Saric, Andrija;Stankovic, Aleksandar
本文提出了一种当信息和通信技术(ICT)组件发生大量故障，使整个系统区域不可见时，估计系统状态的过程。为此，基于流形边界近似方法(MBAM)，提出了一种分析系统能观测性的新方法。MBAM利用信息几何分析数据空间中模型的边界，从而根据可用数据检测不可识别的系统参数和状态。这种方法将基于矩阵的局部方法扩展到全局，使其既能够检测结构上不可识别的参数，也能够检测实际上不可识别的参数(即，以低精度识别)。除了划分可识别/不可识别的状态外，MBAM还减少了模型以移除对不可识别状态变量的引用。为了验证这一过程，通过对物理层和网络系统层进行联合仿真，构建了网络物理系统(CPS)仿真环境。
This paper presents a procedure for estimating the systems state when considerable Information and Communication Technology (ICT) component outages occur, leaving entire system areas unobservable. For this task, a novel method for analyzing system observability is proposed based on the Manifold Boundary Approximation Method (MBAM). By utilizing information geometry, MBAM analyzes boundaries of models in data space, thus detecting unidentifiable system parameters and states based on available data. This approach extends local, matrix-based methods to a global perspective, making it capable of detecting both structurally unidentifiable parameters as well as practically unidentifiable parameters (i.e., identifiable with low accuracy). Beyond partitioning identifiable/unidentifiable states, MBAM also reduces the model to remove reference to the unidentifiable state variables. To test this procedure, cyber-physical system (CPS) simulation environments are constructed by co-simulating the physical and cyber system layers.