Parameter identification of a proposed simplified Bouc-Wen model using a new hybrid algorithm

In this paper, a new hybrid algorithm based on charged system search (CSS) and colliding bodies optimization (CBO) is proposed to parameter identification of highly nonlinear semi-active MR damper. By regarding that in CBO, particles have limited effect with each other, CSS is used to enhanced the search space to increase the particles relationship. To investigate the effectiveness of the proposed new hybrid algorithm, nonlinear modified Bouc-Wen model of MR damper is considered to find its parameters, and compare with those achieved from experimental model of MR damper. Also, in order to simplify the MR damper model, the low-importance parameters in the Bouc-Wen model are eliminated by sensitivity analysis using the importance vectors. Results demonstrate that, the new proposed hybrid algorithm (H- CBO-CSS) has high ability to tackle highly nonlinear problems. Based on the results of the a 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 good ability to estimate damper responses.

Keywords:

parameter identification , Bouc-Wen model , colliding bodies optimization , charged system search , MR damper , importance vector , reliability analysis