A novel hysteretic model for magnetorheological fluid dampers and parameter identification using particle swarm optimization

Publication Type:
Journal Article
Citation:
Sensors and Actuators, A: Physical, 2006, 132 (2), pp. 441 - 451
Issue Date:
2006-11-20
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 Bouc-Wen 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 force-velocity 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. © 2006 Elsevier B.V. All rights reserved.
Please use this identifier to cite or link to this item: