کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
750031 | 894871 | 2006 | 11 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: A novel hysteretic model for magnetorheological fluid dampers and parameter identification using particle swarm optimization A novel hysteretic model for magnetorheological fluid dampers and parameter identification using particle swarm optimization](/preview/png/750031.png)
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.
Journal: Sensors and Actuators A: Physical - Volume 132, Issue 2, 20 November 2006, Pages 441–451