Identification and application of black-box model for a self-sensing damping system using a magneto-rheological fluid damper

In vibration control field, magneto-rheological (MR) fluid dampers are semi-active control devices that have recently begun to receive more attention. This paper presents a black-box model (BBM) for identification of a MR fluid damper and its application to vibrating control systems using that damper with self-sensing behavior. A model named “black-box” is a simple direct modeling method which is designed for a typical MR fluid damper using the self-tuning fuzzy technique. The characteristics of the researched damper are directly estimated through a fuzzy mapping system. In order to improve the accuracy of the proposed model, the back propagation algorithm and gradient descent method were used to train the fuzzy parameters to minimize the model error function. Consequently, the BBM with the optimized parameters can be used as a virtual sensor to measure the damping force of a vibrating control system using the corresponding MR fluid damper. The effectiveness of the proposed self-sensing technique was investigated through a model evaluation and experiments on vibrating systems applied the research MR fluid damper. The modeling results and experimental self-sensing force comparing with actual damping force show that the designed method based on the black-box model can describe well the behavior of the MR fluid damper which is used for the self-sensing damping force control systems.