Abstract
Abstract
The use of dielectric elastomers as integrated actuators and strain sensors offers a simple approach for closed-loop control in a wide range of applications. While a number of approaches for self-sensing have been proposed, the adaptive online algorithm offers an appealing combination of high accuracy and low computational cost. In this work, the recursive least squares algorithm will be applied to capacitive deformation sensing of dielectric elastomers. With the goal of minimizing sampling rate while achieving a set accuracy over a desired range of deformation frequencies, the probe frequency, sampling frequency, and forgetting factor will be optimized. It will be shown that the accuracy is primarily determined by a nondimensionalized variable,
W
¯
, which defines the proportion of a hypothetical deformation cycle that is weighted more heavily by the algorithm. Ultimately, this optimized algorithm will be validated by variably inflating a dielectric elastomer membrane and comparing the algorithm output to membrane deformation measured by video.
Reference11 articles.
1. Integrated sensing and actuation of muscle-like actuators;Gisby,2008
2. Bioinspired tunable lens with muscle-like electroactive elastomers;Carpi;Adv. Funct. Mater.,2011
3. Localised strain sensing of dielectric elastomers in a stretchable soft-touch musical keyboard;Xu,2015
4. Response of dielectric elastomer actuators;Sommer-Larsen,2001
5. An adaptive control method for dielectric elastomer devices;Gisby,2008
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献