Learning the tuned liquid damper dynamics by means of a robust EKF

TL;DR

This paper introduces a robust extended Kalman filter to accurately estimate the dynamics of tuned liquid dampers, enhancing seismic design models by addressing noise and discretization issues.

Contribution

It presents a novel robust EKF approach for modeling TLD dynamics, improving parameter estimation accuracy under uncertain noise conditions.

Findings

Effective estimation of TLD parameters using experimental seismic data

Robust EKF reduces errors caused by model discretization

Improved seismic response modeling for TLD systems

Abstract

The tuned liquid dampers (TLD) technology is a feasible and cost-effective seismic design. In order to improve its efficiency it is fundamental to find accurate models describing their dynamic. A TLD system can be modeled through the Housner model and its parameters can be estimated by solving a nonlinear state estimation problem. We propose a robust extended Kalman filter which alleviates the model discretization and the fact that the noise process is not known. We test the effectiveness of the proposed approach by using some experimental data corresponding to two classical seismic waves, namely the El Centro wave and the Hachinohe wave.