4.7 Article

Fault detection of networked dynamical systems: a survey of trends and techniques

期刊

INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
卷 52, 期 16, 页码 3390-3409

出版社

TAYLOR & FRANCIS LTD
DOI: 10.1080/00207721.2021.1998722

关键词

Networked dynamical systems; fault detection; residuals; network-induced phenomena; communication protocols

资金

  1. Natural Science Foundation of Anhui Province [2108085MA07]
  2. AHPU Youth Top-Notch Talent Support Program [2018BJRC009]
  3. AHPU High-End equipment Intelligent Control Innovation Team [2021CXTD005]

向作者/读者索取更多资源

The fault detection of networked dynamical systems has become a topic of increasing interest due to its importance in maintaining high-quality products and operational safety. This paper provides a survey of fault detection trends and techniques in NDSs, focusing on network-induced phenomena and communication scheduling. Frontier topics such as fault detection with communication protocols and cyber-attacks are extensively discussed, along with future research directions in fault detection.
Fault detection of networked dynamical systems (NDSs) has attracted ever-increasing attention since it can maintain high-quality products as well as operational safety. Considering the utilisation of communication networks, it is desirable to develop engineering-oriented approaches to NDSs subject to the incompleteness from network-induced phenomena (NIP) and the sparsity from communication scheduling. As such, this paper presents a survey of trends and techniques of fault detection in NDSs. First, some typical fault detection methods are summarised based on the various residual assessment functions. Then, some interesting developments are systematically reviewed from two aspects, that is, fault detection with NIP and fault detection under various communication scheduling schemes. In addition, some frontier topics are extensively discussed on fault detection with communication protocols, cyber-attacks, and its applications. Finally, several future works of fault detection problems are investigated to motivate future research.

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