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dc.contributorAlberich Carramiñana, Maria
dc.contributor.authorRomo Grau, Eudald
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Matemàtiques
dc.date.accessioned2017-07-27T12:17:07Z
dc.date.available2017-07-27T12:17:07Z
dc.date.issued2017-05
dc.identifier.urihttp://hdl.handle.net/2117/106966
dc.description.abstractHogan recently provided an heuristic technique called family of modes (FOM) to solve model predictive control (MPC) problems under hybrid constraints and underactuation. The goal of this study is to further develop this new method and to expand its usage in the robotics manipulation community. With that objective in mind, we address some of the method's weaknesses, we provide comparison tools to try to compare the method with traditional MPC solving techniques and we provide a simple and systematic technique to set-up the method's parameters. We conclude the study by presenting our the future lines of research, which consist in generalizing the method for more complex systems and testing it's robustness.
dc.language.isoeng
dc.publisherUniversitat Politècnica de Catalunya
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Matemàtiques i estadística
dc.subject.lcshAlgorithms
dc.subject.otherMPC
dc.subject.otherFOM
dc.subject.otherMIQP
dc.subject.otherOptimal Control
dc.subject.otherPlanar Pushing
dc.subject.otherHybridness
dc.subject.otherUnderactuation
dc.titleA learning approach to the FOM problem
dc.typeBachelor thesis
dc.subject.lemacAlgorismes
dc.subject.amsClassificació AMS::68 Computer science::68W Algorithms
dc.identifier.slugFME-1372
dc.rights.accessOpen Access
dc.date.updated2017-07-14T08:13:06Z
dc.audience.educationlevelGrau
dc.audience.mediatorUniversitat Politècnica de Catalunya. Facultat de Matemàtiques i Estadística
dc.contributor.covenanteeMassachusetts Institute of Technology
dc.description.mobilityOutgoing


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