Smart Structures and Systems

  • 제14권1호
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  • Pages.17-37
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  • 2014
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  • 1738-1584(pISSN)
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  • 1738-1991(eISSN)
테크노프레스 (Techno-Press)
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Output-error state-space identification of vibrating structures using evolution strategies: a benchmark study

  • Dertimanis, Vasilis K. (Department of Civil Engineering and Geomatics, Faculty of Engineering and Technology, Cyprus University of Technology)
  • 투고 : 2013.09.11
  • 심사 : 2014.06.25
  • 발행 : 2014.07.25
⟨ 이전 논문 다음 논문 ⟩

초록

In this study, four widely accepted and used variants of Evolution Strategies (ES) are adapted and applied to the output-error state-space identification problem. The selection of ES is justified by prior strong indication of superior performance to similar problems, over alternatives like Genetic Algorithms (GA) or Evolutionary Programming (EP). The ES variants that are being tested are (i) the (1+1)-ES, (ii) the $({\mu}/{\rho}+{\lambda})-{\sigma}$-SA-ES, (iii) the $({\mu}_I,{\lambda})-{\sigma}$-SA-ES, and (iv) the (${\mu}_w,{\lambda}$)-CMA-ES. The study is based on a six-degree-of-freedom (DOF) structural model of a shear building that is characterized by light damping (up to 5%). The envisaged analysis is taking place through Monte Carlo experiments under two different excitation types (stationary / non-stationary) and the applied ES are assessed in terms of (i) accurate modal parameters extraction, (ii) statistical consistency, (iii) performance under noise-corrupted data, and (iv) performance under non-stationary data. The results of this suggest that ES are indeed competitive alternatives in the non-linear state-space estimation problem and deserve further attention.

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참고문헌

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피인용 문헌

  1. Hybrid evolutionary identification of output-error state-space models vol.1, pp.4, 2014, https://doi.org/10.12989/smm.2014.1.4.427
  2. Data-driven uncertainty quantification of structural systems via B-spline expansion 2017, https://doi.org/10.1016/j.compstruc.2017.03.006