Input load identification of nonlinear tower structural system using intelligent inverse estimation algorithm

摘要

An extended inverse estimation algorithm was developed to effectively estimate the unknown input load in nonlinear structural systems. This algorithm combines the extended Kalman filter and intelligent recursive least squares estimator. This study investigated the unknown input load applied on a tower structural system. Nonlinear characteristics will exist in various structural systems. The nonlinear characteristics are particularly more obvious when applying a larger input load. Numerical simulation cases involving different input 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 loads.