Identification and verification of a MR damper using a nonlinear black box model

Nowadays, magneto-rheological (MR) fluid dampers (MRD) are widely used for the semi-active suspension control in vibration community. However, the inherent nonlinear nature of the MRD causes challenges for damping control of the suspension system using this device with high performance. Therefore, the development of an accurate modeling method for a MRD is necessary to take advantage of its unique characteristics. This paper focuses on the development of a nonlinear black box model to identify and verify behaviors of a MR damper. The model is built by using an online self tuning fuzzy (OSTF) method based on neural technique. The behavior of the MRD is directly estimated through the box. A series of experiments and modeling analysis had been done on test rigs to validate the effectiveness of the design nonlinear black box in predicting the damping force.