Simultaneous Self-Sensing of Displacement and Force for Soft Dielectric Elastomer Actuators
Gianluca Rizzello, Federica Fugaro, David Naso, Stefan Seelecke
Abstract
This paper presents a novel self-sensing method for soft actuators based on dielectric elastomer (DE) membranes. The proposed self-sensing scheme permits the reconstruction of both membrane force and displacement during actuation, based on voltage and current measurements only. The simultaneous self-sensing of displacement and force allows one to implement interaction control strategies without the need for additional electro-mechanical transducers. To achieve this goal, an online estimation algorithm based on recursive least squares is implemented to reconstruct the membrane capacitance from voltage and current measurements. Subsequently, mathematical models are developed to relate the capacitance to membrane displacement and force. Several modeling approaches are compared, ranging from physics-based to black box ones (i.e., Hammerstein-Wiener models and neural networks), in order to evaluate which strategy maximizes the estimation accuracy. After discussing the complete self-sensing algorithm, experimental validation is performed on a prototype consisting of a cone DE membrane.
BibTeX
@inproceedings{ral2018_simultaneousself,
title = {Simultaneous Self-Sensing of Displacement and Force for Soft Dielectric Elastomer Actuators},
author = {Gianluca Rizzello and Federica Fugaro and David Naso and Stefan Seelecke},
booktitle = {RA-L 2018},
year = {2018}
}