Smart Structures and Systems

  • 제28권5호
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  • Pages.617-629
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  • 2021
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  • 1738-1584(pISSN)
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  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
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DOI QR코드

DOI QR Code

A new hybrid model for MR elastomer device and parameter identification based on improved FOA

  • Yu, Yang (School of Civil and Environmental Engineering, University of Technology Sydney) ;
  • Yousefi, Amir M. (Centre for Infrastructure Engineering, Western Sydney University) ;
  • Yi, Kefu (School of Automotive and Mechanical Engineering, Changsha University of Science and Technology) ;
  • Li, Jianchun (School of Civil and Environmental Engineering, University of Technology Sydney) ;
  • Wang, Weiqiang (College of Water Conservancy and Hydropower Engineering, Hohai University) ;
  • Zhou, Xinxiu (Research Institute for Frontier Science, Beihang University)
  • 투고 : 2021.02.19
  • 심사 : 2021.07.15
  • 발행 : 2021.11.25
⟨ 이전 논문 다음 논문 ⟩

초록

A new hysteresis model based on curve fitting method is presented in this work to portray the greatly nonlinear and hysteretic relationships between shear force and displacement responses of the magnetorheological (MR) elastomer base isolator. Compared with classical hysteresis models such as Bouc-Wen or LuGre friction model, the proposed model combines the hyperbolic sine function and Gaussian function to model the hysteretic loops of the device responses, contributing to a great decline of model parameters. Then, an improved fruit fly optimization algorithm (FOA) is proposed to optimize the model parameters, in which a self-adaptive step is employed rather than the fixed step to balance the global and local optimum search abilities of algorithm. Finally, the experimental results of the device under both harmonic and random excitations are used to verify the performance of the proposed hybrid model and parameter identification algorithm with the satisfactory results.

키워드

과제정보

The research described in this paper was funded by the Australian Research Council (Grant No. DP150102636) and the Natural Science Foundation of China (Grant No. 52002036). Besides, Dr. Yancheng Li of University of Technology Sydney is appreciated for the help in device design and test.

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