Bias-dependent impedance model for ionic polymer-metal composites

Abstract

Ionic polymer-metal composites (IPMCs) are a novel class of soft sensing and actuation materials with promising applications in robotic and biomedical systems. In this paper, we present a model for nonlinear electrical dynamics of IPMC actuators, by applying perturbation analysis on the dynamics-governing partial differential equation (PDE) around a given bias voltage. By approximating the steady-state electric field under the bias with a piecewise linear function, we derive a linear PDE for the perturbed charge dynamics, which has piecewise constant coefficients and coefficients linear in the spatial variable. Through power series expansion, we solve the PDE to get the charge distribution up to any prescribed order. The perturbed electric field and current are subsequently obtained, which result in a bias-dependent impedance model. This model captures the nonlinear nature of the IPMC electrical dynamics and degenerates to the linear model when the bias is zero. The model predicts that, as the bias voltage increases, both the magnitude and the phase delay of the impedance decrease. These trends are quantitatively verified in experiments, where excellent agreement is achieved between the experimental measurements and model predictions.

Document Details

Document Type
Pub Defense Publication
Publication Date
Jun 15, 2012
Source ID
10.1063/1.4730339

Entities

People

  • Xiaobo Tan
  • Yannick Kengne Fotsing

Organizations

  • Michigan State University
  • Office of Naval Research

Tags

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Calculus or Mathematical Analysis
  • Plasma Physics.

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference
  • AI & ML - Machine Learning Algorithms
  • Autonomy
  • Biotechnology