Reliability-based simplification of Bouc-Wen model and parameter identification using a new hybrid algorithm

Abstract

In this paper, a new hybrid algorithm based on charged system search (CSS) and colliding bodies optimization (CBO) is proposed to identify the parameters of a highly nonlinear semi-active magneto-rheological damper. As particles have limited effect on each other in CBO, CSS is used to enhance the search space which increases the correlation of particles. To investigate the robustness of the proposed new hybrid algorithm, first, the benchmark mathematical functions are used. Then, a modified Bouc-Wen model of MR damper is considered to find its parameters, based on numerically generated experimental data of MR damper. Also, by exploiting the sensitivity analysis and using the importance vector, the low importance parameters in the Bouc-Wen model are eliminated which makes the MR damper model simpler. Results demonstrate that the new proposed hybrid algorithm (H-CBO-CSS) is greatly capable to tackle highly nonlinear problems. Based on the results of the α importance vector, a simplified model is proposed and its parameters are identified using the presented H-CBO-CSS algorithm. The simplified proposed model also has a high capability of estimating damper responses.