Vis enkel innførsel

dc.contributor.authorMathisen, Siri Gulaker
dc.contributor.authorGros, Sebastien
dc.contributor.authorJohansen, Tor Arne
dc.date.accessioned2021-02-09T13:56:59Z
dc.date.available2021-02-09T13:56:59Z
dc.date.created2020-12-21T12:39:25Z
dc.date.issued2020
dc.identifier.issn0921-0296
dc.identifier.urihttps://hdl.handle.net/11250/2726948
dc.description.abstractTo be able to recover a fixed-wing unmanned aerial vehicle (UAV) on a small space like a boat deck or a glade in the forest, a steep and precise descent is needed. One way to reduce the speed of the UAV during landing is by performing a deep-stall landing manoeuvre, where the lift of the UAV is decreased until it is unable to keep the UAV level, at the same time as the drag is increased to minimize the speed of the UAV. However, this manoeuvre is highly nonlinear and non-trivial to perform with high precision. To solve this, an on-line nonlinear model predictive controller (NMPC) is implemented to guide the UAV in the landing phase, receiving inputs from the autopilot and guiding the UAV using pitch and throttle references. The UAV is guided along a custom path to a predefined deep-stall landing start point and performs a guided deep-stall. The simulation results show that the NMPC guides the UAV in a deep-stall landing with good precision and low speed, and that the results depend on a correct prediction model for the controller.en_US
dc.language.isoengen_US
dc.publisherSpringeren_US
dc.titlePrecision Deep-Stall Landing of Fixed-Wing UAVs using Nonlinear Model Predictive Controlen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionacceptedVersionen_US
dc.source.journalJournal of Intelligent and Robotic Systemsen_US
dc.identifier.doi10.1007/s10846-020-01264-3
dc.identifier.cristin1862336
dc.relation.projectNorges forskningsråd: 223254en_US
dc.description.localcode"This is a post-peer-review, pre-copyedit version of an article. Locked until 17.12.2021 due to copyright restrictions. The final authenticated version is available online at: DOI "en_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode1


Tilhørende fil(er)

Thumbnail

Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel