TY  - JOUR
AU  - Su, Tingli
AU  - Zhang, Yao
AU  - Tang, Zhenyun
PY  - 2025
DA  - 2025/04/30
TI  - Parameter Estimation for the Tuned Liquid Damper Model Based on Robust Extended Kalman Filter
JO  - ICCK Transactions on Sensing, Communication, and Control
T2  - ICCK Transactions on Sensing, Communication, and Control
JF  - ICCK Transactions on Sensing, Communication, and Control
VL  - 2
IS  - 2
SP  - 75
EP  - 84
DO  - 10.62762/TSCC.2025.663633
UR  - https://www.icck.org/article/abs/TSCC.2025.663633
KW  - nonlinear state estimation
KW  - robust kalman filter
KW  - TLD
AB  - The Tuned Liquid Damper (TLD) method offers a practical and cost-effective solution for seismic design. Accurate modeling of the TLD system’s dynamic behavior is crucial for optimizing its performance. In this study, the nonlinear dynamics of the TLD system are characterized using the Housner model, with parameters estimated via a nonlinear state estimation approach. To address challenges associated with model discretization and unknown noise processes, we introduce a Robust Extended Kalman Filter (REKF) that incrementally incorporates uncertainties to more accurately capture system dynamics. The proposed method is evaluated through real-time hybrid simulation, employing seismic input signals from the El Centro and Hachinohe ground motions. Comparative analyses indicate that the robust algorithm achieves superior parameter estimation relative to conventional methods, with estimated parameters closely aligning with reference values and resulting in minimal relative error. This work underscores the efficacy of robust algorithms in TLD vibration response analysis and presents a promising approach for dynamic modeling and seismic performance optimization.
SN  - 3068-9287
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  - 

@article{Su2025Parameter,
  author = {Tingli Su and Yao Zhang and Zhenyun Tang},
  title = {Parameter Estimation for the Tuned Liquid Damper Model Based on Robust Extended Kalman Filter},
  journal = {ICCK Transactions on Sensing, Communication, and Control},
  year = {2025},
  volume = {2},
  number = {2},
  pages = {75-84},
  doi = {10.62762/TSCC.2025.663633},
  url = {https://www.icck.org/article/abs/TSCC.2025.663633},
  abstract = {The Tuned Liquid Damper (TLD) method offers a practical and cost-effective solution for seismic design. Accurate modeling of the TLD system’s dynamic behavior is crucial for optimizing its performance. In this study, the nonlinear dynamics of the TLD system are characterized using the Housner model, with parameters estimated via a nonlinear state estimation approach. To address challenges associated with model discretization and unknown noise processes, we introduce a Robust Extended Kalman Filter (REKF) that incrementally incorporates uncertainties to more accurately capture system dynamics. The proposed method is evaluated through real-time hybrid simulation, employing seismic input signals from the El Centro and Hachinohe ground motions. Comparative analyses indicate that the robust algorithm achieves superior parameter estimation relative to conventional methods, with estimated parameters closely aligning with reference values and resulting in minimal relative error. This work underscores the efficacy of robust algorithms in TLD vibration response analysis and presents a promising approach for dynamic modeling and seismic performance optimization.},
  keywords = {nonlinear state estimation, robust kalman filter, TLD},
  issn = {3068-9287},
  publisher = {Institute of Central Computation and Knowledge}
}