DOI QR코드

DOI QR Code

Grey algorithmic control and identification for dynamic coupling composite structures

  • ZY Chen (Guangdong University of Petrochemical Technology, School of Science) ;
  • Ruei-yuan Wang (Guangdong University of Petrochemical Technology, School of Science) ;
  • Yahui Meng (Guangdong University of Petrochemical Technology, School of Science) ;
  • Timothy Chen (School of Science, Guangdong University of Petrochemical Technology)
  • 투고 : 2022.02.26
  • 심사 : 2023.10.16
  • 발행 : 2023.11.25

초록

After a disaster like the catastrophic earthquake, the government have to use rapid assessment of the condition (or damage) of bridges, buildings and other infrastructures is mandatory for rapid feedbacks, rescue and post-event management. Many domain schemes based on the measured vibration computations, including least squares estimation and neural fuzzy logic control, have been studied and found to be effective for online/offline monitoring of structural damage. Traditional strategies require all external stimulus data (input data) which have been measured available, but this may not be the generalized for all structures. In this article, a new method with unknown inputs (excitations) is provided to identify structural matrix such as stiffness, mass, damping and other nonlinear parts, unknown disturbances for example. An analytical solution is thus constructed and presented because the solution in the existing literature has not been available. The goals of this paper are towards access to adequate, safe and affordable housing and basic services, promotion of inclusive and sustainable urbanization and participation, implementation of sustainable and disaster-resilient buildings, sustainable human settlement planning and manage. Simulation results of linear and nonlinear structures show that the proposed method is able to identify structural parameters and their changes due to damage and unknown excitations. Therefore, the goal is believed to achieved in the near future by the ongoing development of AI and control theory.

키워드

과제정보

The authors are grateful for the research grants given to Ruei-Yuan Wang from the Projects of Talents Recruitment of GDUPT, Peoples R China under Grant NO. 2019rc098, and the research grants given to ZY Chen from the Projects of Talents Recruitment of GDUPT (NO. 2021rc002) in Guangdong Province, Peoples R China. as well as to the anonymous reviewers for constructive suggestions.

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