Modeling of Magnetorheological Damper Using Neuro-Fuzzy System

MR damper has so strong nonlinear characteristics owing to the unclear nonlinearity of the MR suspension in it, that it is very difficult to express the direct model. What's more, it is much more difficult for the inverse model. The paper puts forward a novel train of thoughts to identify the inverse model of the MR damper considering the universal approximation ability of fuzzy system. A neuro-fuzzy system is designed to identify the inverse model of MR damper based on Adaptive Neuro-Fuzzy Inference System (ANFIS). The ANFIS system is similar to its physical counterpart of the MR damper with the same number of the inputs and outputs. The numerical simulation demonstrates that proposed neuro-fuzzy system can accurately identify the inverse model of the MR damper for the training data, and well approximate for the checking data. This idea can be also used to model and control other MR damper with its direct model unknown.