Network distance-based simulated annealing and fuzzy clustering for sensor placement ensuring observability and minimal relative degree

Daniel Leitold, Agnes Vathy-Fogarassy, J. Abonyi

Research output: Contribution to journalArticle

8 Citations (Scopus)


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.

Original languageEnglish
Article number3096
JournalSensors (Switzerland)
Issue number9
Publication statusPublished - Sep 14 2018



  • Fuzzy clustering
  • Network science
  • Relative degree
  • Sensor placement
  • Simulated annealing
  • Structural observability

ASJC Scopus subject areas

  • Analytical Chemistry
  • Atomic and Molecular Physics, and Optics
  • Biochemistry
  • Instrumentation
  • Electrical and Electronic Engineering

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