Department of Computer Science and Systems Technology, University of Pannonia, Egyetem u. 10, H-8200 Veszprém, Hungary.
MTA-PE Lendület Complex Systems Monitoring Research Group, University of Pannonia, Egyetem u. 10., POB. 158, H-8200 Veszprém, Hungary.
Sensors (Basel). 2018 Sep 14;18(9):3096. doi: 10.3390/s18093096.
Network science-based analysis of the observability of dynamical systems has been a focus of attention over the past five years. The maximum matching-based approach provides a simple tool to determine the minimum number of sensors and their positions. However, the resulting proportion of sensors is particularly small when compared to the size of the system, and, although structural observability is ensured, the system demands additional sensors to provide the small relative order needed for fast and robust process monitoring and control. In this paper, two clustering and simulated annealing-based methodologies are proposed to assign additional sensors to the dynamical systems. The proposed methodologies simplify the observation of the system and decrease its relative order. The usefulness of the proposed method is justified in a sensor-placement problem of a heat exchanger network. The results show that the relative order of the observability is decreased significantly by an increase in the number of additional sensors.
基于网络科学的动态系统可观测性分析是过去五年的研究重点。基于最大匹配的方法为确定最少传感器数量及其位置提供了一个简单的工具。然而，与系统规模相比，得到的传感器比例特别小，尽管确保了结构可观测性，但系统需要额外的传感器来提供快速和鲁棒过程监测和控制所需的小相对阶。本文提出了两种基于聚类和模拟退火的方法，用于为动态系统分配额外的传感器。所提出的方法简化了系统的观测并降低了其相对阶。所提出方法的有效性在换热器网络的传感器布置问题中得到了验证。结果表明，通过增加额外传感器的数量，可观测性的相对阶数显著降低。
