Please use this identifier to cite or link to this item: doi:10.22028/D291-30915
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Title: A Self-Sensing Approach for Dielectric Elastomer Actuators Based on Online Estimation Algorithms
Author(s): Rizzello, Gianluca
Naso, David
York, Alexander
Seelecke, Stefan
Language: English
Title: IEEE ASME transactions on mechatronics : a joint publication of the IEEE Industrial Electronics Society and the ASME Dynamic Systems and Control Division
Volume: 22
Issue: 2
Startpage: 728
Endpage: 738
Publisher/Platform: IEEE
Year of Publication: 2017
Publikation type: Journal Article
Abstract: This paper develops a position self-sensing approach for a motion actuator based on a dielectric elastomer membrane. The proposed method uses voltage and current measurements to estimate the electrical resistance and capacitance online by means of a high-frequency low-amplitude voltage component injected in the actuation signal. The actual deformation is subsequently reconstructed using a model-based estimate of the electrical parameters implemented on a field programmable gate array platform (FPGA) with a sampling frequency of 20 kHz. The main peculiarity of the approach is the use of recursive identification and filtering algorithms that avoid the need of charge measurements. The self-sensing algorithm is extensively validated on a precision linear-motion actuator, which uses a nonlinear biasing system to obtain large actuation strokes.
DOI of the first publication: 10.1109/TMECH.2016.2638638
URL of the first publication:
Link to this record: hdl:20.500.11880/29128
ISSN: 1941-014X
Date of registration: 12-May-2020
Faculty: NT - Naturwissenschaftlich- Technische Fakultät
Department: NT - Systems Engineering
Professorship: NT - Prof. Dr. Stefan Seelecke
Collections:UniBib – Die Universitätsbibliographie

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