A Novel Hysteretic Model for Magnetorheological Fluid Dampers and Parameter Identification Using Particle Swarm Optimization

Publisher:
Elsevier
Publication Type:
Journal Article
Citation:
Sensors And Actuators A: Physical, 2006, 132 (2), pp. 441 - 451
Issue Date:
2006-01
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2006005052.pdf1.14 MB
Adobe PDF
Non-linear hysteresis is a complicated phenomenon associated with magnetorheological (MR) fluid dampers. A new model for MR dampers is proposed in this paper. For this, computationally-tractable algebraic expressions are suggested here in contrast to the commonly-used BoucWen model, which involves internal dynamics represented by a non-linear differential equation. In addition, the model parameters can be explicitly related to the hysteretic phenomenon. To identify the model parameters, a particle swarm optimization (PSO) algorithm is employed using experimental forcevelocity data obtained from various operating conditions. In our algorithm, it is possible to relax the need for a priori knowledge on the parameters and to reduce the algorithmic complexity. Here, the PSO algorithm is enhanced by introducing a termination criterion, based on the statistical hypothesis testing to guarantee a user-specified confidence level in stopping the algorithm. Parameter identification results are included to demonstrate the accuracy of the model and the effectiveness of the identification process.
Please use this identifier to cite or link to this item: