English   español  
Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/230225
Share/Impact:
Statistics
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

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

Title

Tracking of Unicycle Robots Using Event-Based MPC with Adaptive Prediction Horizon

AuthorsSun, Zhongqi; Xia, Yuanqing; Dai, Li; Campoy, Pascual
KeywordsAdaptive prediction horizon
Event-triggered control
Model predictive control (MPC)
Self-triggered control
Unicycle robots
Issue DateApr-2020
PublisherIEEE
CitationIEEE/ASME Transactions on Mechatronics 25 (2): 739-749 (2020)
AbstractIn this article, we propose two event-based model predictive control (MPC) schemes with adaptive prediction horizon for tracking of unicycle robots with additive disturbances. The schemes are able to reduce the computational burden from two aspects: reducing the frequency of solving the optimization control problem (OCP) to relieve the computational load and decreasing the prediction horizon to decline the computational complexity. Event-triggering and self-triggering mechanisms are developed to activate the OCP solver aperiodically, and a prediction horizon update strategy is presented to decrease the dimension of the OCP in each step. The proposed schemes are tested on a networked platform to show their efficiency.
Publisher version (URL)https://doi.org/10.1109/TMECH.2019.2962099
URIhttp://hdl.handle.net/10261/230225
DOI10.1109/TMECH.2019.2962099
ISSN1083-4435
E-ISSN1941-014X
Appears in Collections:(CAR) Artículos
Files in This Item:
File Description SizeFormat 
Acceso_Restringido.pdfArtículo restringido15,35 kBAdobe PDFThumbnail
View/Open
Show full item record
Review this work
 


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