Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/79996
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dc.contributorDepartment of Mechanical Engineering-
dc.creatorLi, B-
dc.creatorZhou, W-
dc.creatorSun, J-
dc.creatorWen, CY-
dc.creatorChen, CK-
dc.date.accessioned2018-12-21T07:14:34Z-
dc.date.available2018-12-21T07:14:34Z-
dc.identifier.issn1424-8220-
dc.identifier.urihttp://hdl.handle.net/10397/79996-
dc.language.isoenen_US
dc.publisherMolecular Diversity Preservation International (MDPI)en_US
dc.rights© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Li, B., Zhou, W., Sun, J., Wen, C. -., & Chen, C. -. (2018). Development of model predictive controller for a tail-sitter VTOL UAV in hover flight. Sensors (Switzerland), 18(9), 2859, 1-21 is available at https://dx.doi.org/10.3390/s18092859en_US
dc.subjectFlight experimenten_US
dc.subjectHardware-in-loop (HIL) simulationen_US
dc.subjectModel predictive control (MPC)en_US
dc.subjectTail-sitteren_US
dc.subjectUnmanned aerial vehicles (UAV)en_US
dc.subjectVertical takeoff and landing (VTOL)en_US
dc.titleDevelopment of model predictive controller for a tail-sitter VTOL UAV in hover flighten_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage1-
dc.identifier.epage21-
dc.identifier.volume18-
dc.identifier.issue9-
dc.identifier.doi10.3390/s18092859-
dcterms.abstractThis paper presents a model predictive controller (MPC) for position control of a vertical take-off and landing (VTOL) tail-sitter unmanned aerial vehicle (UAV) in hover flight. A ‘cross’ configuration quad-rotor tail-sitter UAV is designed with the capabilities for both hover and high efficiency level flight. The six-degree-of-freedom (DOF) nonlinear dynamic model of the UAV is built based on aerodynamic data obtained from wind tunnel experiments. The model predictive position controller is then developed with the augmented linearized state-space model. Measured and unmeasured disturbance model are introduced into the modeling and optimization process to improve disturbance rejection ability. The MPC controller is first verified and tuned in the hardware-in-loop (HIL) simulation environment and then implemented in an on-board flight computer for real-time indoor experiments. The simulation and experimental results show that the proposed MPC position controller has good trajectory tracking performance and robust position holding capability under the conditions of prevailing and gusty winds.-
dcterms.accessRightsopen access-
dcterms.bibliographicCitationSensors (Switzerland), Sept. 2018, v. 18, no. 9, 2859, p. 1-21-
dcterms.isPartOfSensors (Switzerland)-
dcterms.issued2018-09-
dc.identifier.scopus2-s2.0-85052705792-
dc.identifier.artn2859-
dc.description.validate201812 bcrc-
dc.description.oaVersion of Record-
dc.identifier.FolderNumbera0716-n05-
dc.identifier.SubFormID1042-
dc.description.fundingSourceSelf-funded-
dc.description.pubStatusPublished-
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