Construction Techniques and Statistical Analysis of Dielectric Elastomer Actuators

In this study, a series of experiments were conducted to investigate and improve upon existing construction methods of dielectric elastomer actuators (DEAs). First, a proof of concept was built, which utilized a DEA as an active diaphragm to reproduce sound. Next, two electrode sizes and construction methods were compared via statistical analysis of electrode strain. In an attempt to develop an easier and more efficacious electrode construction method, the substance used for electrodes was then dissolved in six solvents. A commercially available graphite spray was compared against the solutions and determined to be the most promising on the basis of measured surface conductivity and observed particle dispersion. Finally, an actuator was tested with graphite spray electrodes; it was discovered that the spray hardens when dried and was thus not able to produce in-plane deformation

Iterative Learning Control of Hysteresis in Piezoelectric Actuators

We develop convergence criteria of an iterative learning control on the whole desired trajectory to obtain the hysteresis-compensating feedforward input in hysteretic systems. In the analysis, the Prandtl-Ishlinskii model is utilized to capture the nonlinear behavior in piezoelectric actuators. Finally, we apply the control algorithm to an experimental piezoelectric actuator and conclude that the tracking error is reduced to 0.15% of the total displacement, which is approximately the noise level of the sensor measurement

Polymer sensorised microgrippers using SMA actuation

Abstract-In this paper a polymer sensorised microgripping tool for micromanipulation is presented. The gripper structure is made by moulding of polyurethane in silicon moulds by the technique of Shape Deposition Manufacturing (SDM), in which the force sensing elements and part of the actuator (in this case, microstrain gauges and SMA (Shape Memory Alloy) wire, respectively) are embedded into the microgripper in one process step. The actuation principle for the microgripper is an SMA wire. The advantages of the fabrication process are low cost and manufacture cycle time. This paper details the technique for fabrication of the microgripper to produce prototypes. These prototypes were then tested and characterised in terms of force output, hysteresis and repeatability. A further miniaturised unsensorised microgripper based on the same actuation principle and fabrication process (but less than half the size) was fabricated to demonstrate the possibility of further downscaling

System identification of a class of Wiener systems with hysteretic nonlinearities

Existing works on Wiener system identification have essentially been focused on the case where the output nonlinearity is memoryless. When memory nonlinearities have been considered, the focus has been restricted to backlash like nonlinearities. In this paper, we are considering Wiener systems where the output nonlinearity is a general hysteresis operator captured by the well-known Bouc-Wen model. The Wiener system identification problem is addressed by making use of a steady-state property, obtained in periodic regime, referred to as hysteretic loop assumption'. The complexity of this problem comes from the system nonlinearity as well as its unknown parameters that enter in a non-affine way in the model. It is shown that the linear part of the system is accurately identified using a frequency method. Then, the nonlinear hysteretic subsystem is identified, on the basis of a parameterized representation, using a prediction-error approach.Postprint (author's final draft

Adaptive inverse modeling of a shape memory alloy wire actuator and tracking control with the model

It is well known that the Preisach model is useful to approximate the effect of hysteresis behavior in smart materials, such as piezoactuators and Shape Memory Alloy(SMA) wire actuators. For tracking control, many researchers estimate a Preisach model and then compute its inverse model for hysteresis compensation. However, the inverse of its hysteresis behavior also shows hysteresis behavior. From this idea, the inverse model with Kransnoselskii-Pokrovskii(KP) model, a developed version of Preisach model, can be used directly for SMA position control and avoid the inverse operation. Also, we propose another method for the tracking control by approximating the inverse model using an orthogonal polynomial network. To estimate and update the weight parameters in both inverse models, a gradient-based learning algorithm is used. Finally, for the SMA position control, PID controller, adaptive controllers with KP model and adaptive nonlinear inverse model controller are compared experimentally