English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/209366
logo share SHARE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE
Exportar a otros formatos:


Feedback-Error Learning Control for Powered Assistive Devices

AuthorsNuno Fernandes, Pedro; Figueiredo, Joana; Moreno, Juan Camilo ; Peixoto Santos, Cristina
KeywordsGait rehabilitation
Robotic assistive devices
Human-centered robotics
Feedback error learning control
Neural network
Issue Date26-Sep-2019
CitationXV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019 in Coimbra, Portugal, 26 September 2019
AbstractActive orthoses (AOs) are becoming relevant for user-oriented training in gait rehabilitation. This implies efficient responses of AO¿s low-level controllers with short time modeling for medical applications. This thesis investigates, in an innovative way, the performance of Feedback-Error Learning (FEL) control to time-effectively adapt the AOs¿ responses to user-oriented trajectories and changes in the dynamics due to the interaction with the user. FEL control comprises a feedback PID controller and a neural network feedforward controller to promptly learn the inverse dynamics of two AOs. It was carried out experiments with able-bodied subjects walking on a treadmill and considering external disturbances to user-AO interaction. Results showed that the FEL control effectively tracked the user-oriented trajectory with position errors between 5% to 7%, and with a mean delay lower than 25 ms. Compared to a single PID control, the FEL control decreased by 16.5% and 90.7% the position error and delay, respectively. Moreover, the feedforward controller was able to learn the inverse dynamics of the two AOs and adapt to variations in the user-oriented trajectories, such as speed and angular range, while the feedback controller compensated for random disturbances. FEL demonstrated to be an efficient low-level controller for controlling AOs during gait rehabilitation.
DescriptionTrabajo presentado en XV Mediterranean Conference on Medical and Biological Engineering and Computing – MEDICON 2019 en Coimbra, Portugal el 26 de Septiembre de 2019.
Publisher version (URL)http://dx.doi.org/10.1007/978-3-030-31635-8_238
Identifiersdoi: 10.1007/978-3-030-31635-8_238
isbn: 978-3-030-31634-1
Appears in Collections:(IC) Comunicaciones congresos
Files in This Item:
File Description SizeFormat 
accesoRestringido.pdf15,38 kBAdobe PDFThumbnail
Show full item record
Review this work

WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.