Modeling and Inverse Compensation of Temperature-Dependent Ionic Polymer-Metal Composite Sensor Dynamics

Ionic polymer-metal composites (IPMCs) have intrinsic sensing capabilities. Like many other sensing materials, however, IPMC sensors demonstrate strong temperature-dependent behaviors. In this paper, we present the first systematic studies on temperature-dependent IPMC sensing dynamics. A cantilevered IPMC beam, soaked in a water bath with controlled temperature, is excited mechanically at its tip. The empirical frequency response of the sensor, with the tip displacement as an input and the short-circuit current as an output, shows a clear dependence on the bath temperature. The sensing dynamics is modeled with a transfer function with temperature-dependent coefficients. By fitting the values of the coefficients at a set of test temperatures, we capture the temperature dependence of the coefficients with polynomial functions, which can be used to predict the sensing dynamics at other temperatures. We also investigate the inversion of the sensing dynamics, for extracting the mechanical signal given the sensor output. A stable but noncausal inversion algorithm is applied to deal with the unstable zeros of the original sensing dynamics. Inversion with finite preview time is further explored to achieve near real-time decoding of the sensor output. Experimental results with both harmonic stimuli and free vibrations have validated the effectiveness of the proposed modeling and inversion schemes for IPMC sensors under different temperatures.