Fuzzy approximation of MR damper

An MR damper has strong nonlinearity between inputs and output owing to the unknown nonlinearity of the MR suspension in it. It is quite difficult to describe the direct model of the MR damper, however, it is much more difficult for the inverse model. The paper presents a novel train of thoughts to approach to the inverse model of the MR damper by using the universal approximation of a kind of fuzzy system. Then two different fuzzy systems are designed to approximate the direct model and the inverse one on the basis of adaptive neuro-fuzzy inference system (ANFIS). These two ANFIS are similar to their physical counterparts of the MR damper, just considering the number of the inputs and output. The numerical simulation proves that such two fuzzy systems can accurately approximate the direct model and inverse model of the MR damper for the train data, and well approximate for the check data. This idea can be extended to other models of MR dampers. Furthermore, it can be also used to model and control other MR damper with its direct model unknown.