Adaptive intelligent control of ionic polymer–metal composites

Abstract

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%.

Intelligent Control of Electroactive Polymer Actuators Based on Fuzzy and Neurofuzzy Methodologies

“…Therefore, the use of classical model based control systems can introduce errors and inaccuracies into the system [1,4]. Intelligent controllers such as those based on fuzzy logic or neural networks operate without any dependence upon system models and are thus well suited to the control of polymer actuators [2,5,6].…”

“…To be able to design and optimise a controller to compensate for system dynamics, a Model Reference Adaptive Control (MRAC) scheme utilising a genetic algorithm for optimisation was developed for tracking control of an IPMC type polymer actuator [6]. Whilst these actuators differ from the PPy type, the control scheme is equally applicable.…”

“…Combine antecedent input variables x 1 , x 2 , ... , x n to determine the firing strength (rule weight) using a T-norm product operator for AND (5) and S-norm probabilistic OR method operator for OR (6).…”

Integrated Sensing for IPMC Actuators Using Strain Gages for Underwater Applications

“…Nonintegrated sensors include lasers [23], charge-coupled device (CCD) cameras [24], or force sensors [25] that may or may not come into physical contact with the actuator, to measure the IPMC's response for feedback control. Laser displacement sensors are by far the most common because they are ubiquitous and easy to use.…”

“…Additionally, the output can vary with surface reflectivity. Charge-coupled device cameras and computer software can be used to estimate the IPMC's deformation [24]. Like lasers, they too are bulky and not practical for microautonomous systems.…”