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
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| Filename | Description | Size | |||
|---|---|---|---|---|---|
 | 2006005052.pdf | 1.14 MB |
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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.
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