Ionic polymer metal composite (IPMC) materials are in an early stage of development. Their response as actuators is still very unpredictable. Their dynamic response is still subjected to several critical parameters that vary with time, thus extracting an accurate and repeatable model is very difficult. This paper presents the design and implementation of an adaptive efficient position control system for an IPMC actuator working in underwater conditions. The control system is an model reference adaptive control (MRAC) based on a reference model and an adaptation that controls a 1 cm × 0.5 cm length IPMC strip based on a Nafion 117 Na+ membrane. As the reference model a second-order empirical model of the plant is used. The control system is first simulated and then experimentally implemented within the LabVIEW framework.

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An image processing system for the measurement of small movements of synthetic IPMC materials is presented in this work. The proposed technique is based on extracting the appropriate information from subsequent pictures-frames. Since the time-difference between these pictures is known, it is possiblefor the system to calculate both displacements and speed of the moving part. The processing algorithm implements a fully automated procedure for the localization ofthe point ofinterest (i.e. the edge of a micro-robotic wing) in every frame and then calculates the distance (displacement) between subsequent frames. This method is particularly usefulfor rather large movements ofthe IPMC strips as found in micro-robotic applications. The results obtained by the proposed system are also compared with concurrent measurements by a high accuracy laser positioning system, and have been found quite satisfactory for the specific application (resolution better than 0. 5mm)

The implementation of a real-time measurement system based on visual measurements of displacement of an actuator–cantilever is presented in this paper. This work is aimed at accelerating image processing for the fast tracking of small actuators based on ionic polymer–metal composites using the graphics processing unit (GPU) approach. The proposed processing techniques for point tracking are based on the analysis of subsequent images of the moving item. The area-segmentation approach is used which combines region prediction, successive scanning, edge filtering and match processing. The overall implementation uses the CPU and GPU, while the results achieved indicate that the computation process speeds up by more than 40×. This is a quite useful improvement especially for real-time measurement and control applications of closed-loop systems based on IPMC materials.

Ionic polymer-metal composites (IPMCs) produce large bending motions under a low driving voltage and can be used in underwater applications. In this work, the control ofionic polymer metal composite actuators is investigated from a practical perspective. The control ofIPMC is important in many processes and applications including underwater applications. This work develops an approach for model reference control of IPMCs. The main idea is to settle the behavior of IPMC adjustable from reference model. This strategy is demonstrated on an experimental rig using real time control. Experimental results confirm that a reference control of the IPMC is achievable.