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Sensors 2018, 18(9), 3096; https://doi.org/10.3390/s18093096

Network Distance-Based Simulated Annealing and Fuzzy Clustering for Sensor Placement Ensuring Observability and Minimal Relative Degree

1
Department of Computer Science and Systems Technology, University of Pannonia, Egyetem u. 10, H-8200 Veszprém, Hungary
2
MTA-PE Lendület Complex Systems Monitoring Research Group, University of Pannonia, Egyetem u. 10., POB. 158, H-8200 Veszprém, Hungary
*
Author to whom correspondence should be addressed.
Received: 30 June 2018 / Revised: 11 September 2018 / Accepted: 11 September 2018 / Published: 14 September 2018
(This article belongs to the Special Issue Artificial Intelligence and Machine Learning in Sensors Networks)
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Abstract

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. View Full-Text
Keywords: sensor placement; network science; fuzzy clustering; simulated annealing; structural observability; relative degree sensor placement; network science; fuzzy clustering; simulated annealing; structural observability; relative degree
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Leitold, D.; Vathy-Fogarassy, A.; Abonyi, J. Network Distance-Based Simulated Annealing and Fuzzy Clustering for Sensor Placement Ensuring Observability and Minimal Relative Degree. Sensors 2018, 18, 3096.

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