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http://hdl.handle.net/10261/230225
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Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE | |
Campo DC | Valor | Lengua/Idioma |
---|---|---|
dc.contributor.author | Sun, Zhongqi | es_ES |
dc.contributor.author | Xia, Yuanqing | es_ES |
dc.contributor.author | Dai, Li | es_ES |
dc.contributor.author | Campoy, Pascual | es_ES |
dc.date.accessioned | 2021-02-21T17:19:27Z | - |
dc.date.available | 2021-02-21T17:19:27Z | - |
dc.date.issued | 2020-04 | - |
dc.identifier.citation | IEEE/ASME Transactions on Mechatronics 25 (2): 739-749 (2020) | es_ES |
dc.identifier.issn | 1083-4435 | - |
dc.identifier.uri | http://hdl.handle.net/10261/230225 | - |
dc.description.abstract | In 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. | es_ES |
dc.description.sponsorship | National Natural Science Foundation Projects of International Cooperation and Exchanges; 10.13039/501100004826 - Natural Science Foundation of Beijing Municipality; 10.13039/501100001809 - National Natural Science Foundation of China; 10.13039/501100012166 - National Basic Research Program of China (973 Program); 10.13039/501100012659 - Foundation for Innovative Research Groups of the National Natural Science Foundation of China. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | Institute of Electrical and Electronics Engineers | es_ES |
dc.relation.isversionof | Postprint | es_ES |
dc.rights | closedAccess | es_ES |
dc.subject | Adaptive prediction horizon | es_ES |
dc.subject | Event-triggered control | es_ES |
dc.subject | Model predictive control (MPC) | es_ES |
dc.subject | Self-triggered control | es_ES |
dc.subject | Unicycle robots | es_ES |
dc.title | Tracking of Unicycle Robots Using Event-Based MPC with Adaptive Prediction Horizon | es_ES |
dc.type | artículo | es_ES |
dc.identifier.doi | 10.1109/TMECH.2019.2962099 | - |
dc.description.peerreviewed | Peer reviewed | es_ES |
dc.relation.publisherversion | https://doi.org/10.1109/TMECH.2019.2962099 | es_ES |
dc.identifier.e-issn | 1941-014X | - |
dc.relation.csic | Sí | es_ES |
oprm.item.hasRevision | no ko 0 false | * |
dc.contributor.orcid | Sun, Zhongqi [0000-0002-6756-2791] | es_ES |
dc.contributor.orcid | Xia, Yuanqing [0000-0002-5977-4911] | es_ES |
dc.contributor.orcid | Dai, Li [0000-0002-7268-7548] | es_ES |
dc.contributor.orcid | Campoy, Pascual [0000-0002-9894-2009] | es_ES |
dc.type.coar | http://purl.org/coar/resource_type/c_6501 | es_ES |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.fulltext | No Fulltext | - |
item.cerifentitytype | Publications | - |
item.openairetype | artículo | - |
item.languageiso639-1 | en | - |
item.grantfulltext | none | - |
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