Ionic Polymer-Metal Composite (IPMC) is a kind of smart material which can be used as sensors or actuators. As IPMC is very flexible and can produce larger electric signal when it is deformed, it is more suitable to be used as sensors to measure deformation, displacement and flow rate. However, hysteresis existing in IPMC will deteriorate the performance of the sensor. In this paper, a neural network model based compensator is proposed to reduce the effect of hysteresis. In the compensation scheme, a method of expanded input space is introduced to transform the multi-valued mapping of hysteresis to a one-to-one mapping. The corresponding theory of the construction of the expanded input space is illustrated. Then, based on the expanded input space, the inverse model based compensator is then constructed. Moreover, a geometric compensation method is proposed to compensate for the measuring error of the laser sensor on IPMC chip. Finally, experimental results are presented to validate the proposed method of hysteresis compensation for IPMC sensors.