Recent technological advances in miniaturized actuators and sensors have enabled the development of cooperative systems, in which a complex global task is achieved through the cooperation of several microactuators. Achieving system miniaturization while maintaining the desired actuation/sensor and cooperative functionality, however, is in general a highly challenging task. To reach this goal, one viable approach consists of implementing transducers based on intelligent materials, such as dielectric elastomers (DE). By designing a miniaturized array of DE membrane taxels, their simultaneous actuation and sensing capabilities can be used to develop flexible, large deformation, energy-efficient, and multi-functional cooperative systems. In addition, the high flexibility of DE material makes the developed system highly suitable for new fields of application, such as wearables and soft robotics.
In order to properly understand and optimize DE array systems, accurate models and simulation tools play a fundamental role. Due to the strongly nonlinear behavior of the material, however, DE modeling is generally highly challenging. In addition, the electro-mechanical coupling and the neighboring effects existing between closely packed actuators further complicates the overall modeling task.
In this paper, we present a physics-based model for an array of three DEAs. Such a model represents the first step towards the development of a complex cooperative matrix actuator. Through the proposed model, it is possible to describe the electromechanical coupling existing between the DE elements, and how such a cupling affects the complete system performance. These interactions depend on several design parameters, such as the size of the individual membranes, their relative spacing, and the mechanical pre-tensioning. After presenting the model, the influence of geometrical parameters on the spatial coupling response is studied by means of numerical simulations. The developed model will allow, in a future stage, to effectively design and optimize cooperative DE systems.