A Novel Coupled State/Load/Parameter Identification Method Based on the Improved Particle Filter Algorithm

Abstract

Abstract There have been increasing research studies focusing on the identification of structural load with uncertain model in recent years. This paper presents a novel approach based on the improved Particle Filter (PF) algorithm for the nonlinear structural system. The main strategy of the approach is the fusion of the weighted least-square algorithm and the conventional PF algorithm. The weighted least-square algorithm is derived for the estimation of the unknown loads, and the PF algorithm is used for the identification of the augmented states which includes the structural displacement, velocity and unknown parameters. Additionally, the parallel algorithm is adopted for the improvement of computing speed, and a resampling step is also used for alleviating the degeneracy of the particles to improve the accuracy. A numerical example modelling as a four-story hysteretic shear-beam building is studied to validate the capability of the presented approach.