Intelligent system identification for an axis of car passive suspension system using real data

This paper presents an intelligent system identification using multilayer perceptron neural network algorithm for an axis car passive suspension model. Nonlinear autoregressive with exogenous input (NARX) model were assumed for the system in order to determine the multilayer perceptron neural network structure. The intelligent system identification constructed for NARX model used real input output data acquired by driving a car on a special road event. The results show that the method proposed is suitable for modeling a quarter car passive suspension systems.