Adaptive intelligent control of ionic polymer-metal composites

Electroactive polymers undergo physical deformation in response to external voltage stimuli. These electrically activated polymers possess extraordinary features making them capable of use as lightweight sensors and actuators in manifold applications. The characteristics of applied voltage and environmental conditions, especially the moisture content surrounding the polymer, have a combined influence on the dynamical behavior of these polymers. In order to characterize these polymers under varying environmental conditions, this paper discusses the experimental procedure and modeling techniques used to derive a representative model. Validation of the model derived is provided by comparison tests of the simulated model results and those for experimental specimens. Ionic polymer-metal composites are used for this humidity and electrodynamical study. Insight into the numerous applications of electroactive polymers as actuators is given. The extended model allows for controller design for typical tracking problems. The control architecture presented includes a model reference adaptive scheme along with pole-placement control strategies for achieving the goal of tracking. A genetic algorithm approach is employed to carry out the optimization for the control action. The resulting tracking control of ionic polymer-metal composites, acting as actuators, is simulated. Simulations show that tracking results can be achieved with a correlation of 99% and a root mean square error of less than 30%.