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The DOI matches its Crossref record; 34 of the 37 references it cites were found in a registry or an index.

Optimization of tuned mass damper parameters for floating wind turbines by using the artificial fish swarm algorithm

Abstract

Abstract In this study, the vibration control of floating wind turbines (FWTs) and the influence of the tuned mass damper (TMD) location on the displacements and loads of key parts of an FWT are investigated. First, a complete wind turbine model is built and the drivetrain model is validated. Second, a six-degrees-of-freedom dynamic model is established for FWTs according to the Lagrange equation by considering the combined effect of the tower, platform, and TMD motions. The dynamic model is used to optimize the TMD parameters. Third, the unknown parameters of the proposed model are estimated using the Levenberg–Marquardt method. Fourth, by taking the minimum standard deviation of the fore–aft displacement at the top of the tower as the control objective, the mass, damping, and stiffness coefficients of the TMD are optimized using the artificial fish swarm algorithm. Finally, cosimulation is performed for five load cases. The results suggest that the TMD location and load case affect the mitigation effect for the evaluation indices.

Overview

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Registry

Crossref · 10.1016/j.oceaneng.2018.08.031

Cites

34 of 34 references verified0 citation errors · 0 not checkable

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Citations

Cites

Show all 37 references

Research works printed but not linked: 2

  1. Ranganathan, 2004, The levenberg-marquardt algorithm, Tutoral on Lm Algorithm, 11, 101
  2. Tang, 2006, Analysis on control of wind induced vibration of a super-tall building with TMD, J. Vib. Shock, 25, 16

Metadata

Authors
Jin, X., Xie, S., He, J., Lin, Y., Wang, Y., & Wang, N.
Affiliations
Chongqing University (CN)
Corresponding author
Jin, Xin
Venue
Ocean Engineering
Publisher
Elsevier BV
Published
2018-11
Volume
167
Pages
130-141
ISSN
0029-8018 (ISSN-L)
OpenAlex
W2889431161
Cited by
58
References
37
Citations by year
2026: 10 · 2025: 6 · 2024: 8 · 2023: 7 · 2022: 8 · 2021: 7 · 2020: 6 · 2019: 5 · 2018: 1
FWCI
4.27
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
Ocean Engineering (publishedVersion)
Funders
  • Scientific and Technological Research Program of the Chongqing Municipal Education Commission (KJ1605501)
  • National Natural Science Foundation of China (51005255)
Topics
  • Physical Sciences › Engineering › Civil and Structural Engineering › Vibration Control and Rheological Fluids
  • Physical Sciences › Engineering › Ocean Engineering › Wave and Wind Energy Systems
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Wind Turbine Control Systems
Keywords
floating wind turbines, tuned mass damper, vibration control, artificial fish swarm algorithm, TMD parameter optimization, structural loads, parameter estimation, Levenberg-Marquardt algorithm, co-simulation

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CoChat. (2026). Citation check: Optimization of tuned mass damper parameters for floating wind turbines by using the artificial fish swarm algorithm. https://app.cochat.ai/papers/10.1016/j.oceaneng.2018.08.031
The paper
Jin, X., Xie, S., He, J., Lin, Y., Wang, Y., & Wang, N. (2018). Optimization of tuned mass damper parameters for floating wind turbines by using the artificial fish swarm algorithm. Ocean Engineering. https://doi.org/10.1016/j.oceaneng.2018.08.031

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.