Abstract: Magnetorheological damper is a new kind of smart device for vibration control. Through characteristic testing of MR damper, force-displacement and force-velocity relationship at different current is researched; the main features of friction-type MR damper are analyzed. A forward model and an inverse model of MR damper are established by using BP neural network. Simulation results show that the neural network model can accurately predict force and current of MR damper, so the approach is effective. Comparing with the existing model, the features of the model built in this paper are high accuracy and easy calculation.

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