Neural Network Based Modeling of Hysteresis in Smart Material Based Sensors

Hysteresis is a nonlinear phenomenon which is involved with dynamics, non-smoothness and multi-valued mapping. It usually exists in elastic materials, smart materials, and energy-storage materials. For describing the characteristic of hysteresis, a basis function based neural network model is proposed in this paper. In this method, the multi-valued mapping of hysteresis is transferred into a one-to-one mapping with an expanded input space involving the input variable and a constructed hysteretic auxiliary function. Thus, the neural network can be employed to approximate the characteristic of hysteresis. Finally, the method is used to the modeling of hysteresis in a smart material based sensor.