Bouc-Wen Model Parameter Identification for a MR Fluid Damper Using Particle Swarm Optimization

This paper present parameter identification fitting which are employed into a current model. Irregularity hysteresis of Bouc-Wen model is colloquial with magneto-rheological (MR) fluid damper. The model parameters are identified with a Particle Swarm Optimization (PSO) which involves complex dynamic representation. The PSO algorithm specifically determines the best fit value and decrease marginal error which compare to the experimental data from various operating conditions in a given boundary.