Buy article PDF
The purchased file will be sent to you
via email after the payment is completed.
US$ 35
|
Wind and Structures Volume 17, Number 4, October 2013 , pages 451-464 DOI: https://doi.org/10.12989/was.2013.17.4.451 |
|
|
|
Nonlinear structural system wind load input estimation using the extended inverse method |
||
Ming-Hui Lee
|
||
| Abstract | ||
| This study develops an extended inverse input estimation algorithm with intelligent adaptive fuzzy weighting to effectively estimate the unknown input wind load of nonlinear structural systems. This algorithm combines the extended Kalman filter and recursive least squares estimator with intelligent adaptive fuzzy weighting. This study investigated the unknown input wind load applied on a tower structural system. Nonlinear characteristics will exist in various structural systems. The nonlinear characteristics are particularly more obvious when applying larger input wind load. Numerical simulation cases involving different input wind load types are studied in this paper. The simulation results verify the nonlinear characteristics of the structural system. This algorithm is effective in estimating unknown input wind loads. | ||
| Key Words | ||
| fuzzy estimator; fuzzy Kalman filter; least square method; fuzzy logic | ||
| Address | ||
| Ming-Hui Lee : Department of Civil Engineering, Chinese Military Academy, Fengshan, Kaohsiung, Taiwan, R.O.C. | ||