Model predictive control of a tilt-rotor UAV for load transportation
| dc.creator | Richard Andrade | |
| dc.creator | Guilherme Vianna Raffo | |
| dc.creator | Julio E. Normey-Rico | |
| dc.date.accessioned | 2025-03-18T15:56:52Z | |
| dc.date.accessioned | 2025-09-08T23:57:35Z | |
| dc.date.available | 2025-03-18T15:56:52Z | |
| dc.date.issued | 2016 | |
| dc.identifier.doi | 10.1109/ECC.2016.7810612 | |
| dc.identifier.issn | 2996-8895 | |
| dc.identifier.uri | https://hdl.handle.net/1843/80741 | |
| dc.language | eng | |
| dc.publisher | Universidade Federal de Minas Gerais | |
| dc.relation.ispartof | European Control Conference (ECC) | |
| dc.rights | Acesso Restrito | |
| dc.subject | Engenharia elétrica | |
| dc.subject | Aeronave não tripulada | |
| dc.subject | Controle automático | |
| dc.subject | Teoria do controle | |
| dc.subject.other | Unmanned Aerial Vehicles | |
| dc.subject.other | Predictive Control | |
| dc.subject.other | Model Predictive Control | |
| dc.subject.other | Load Transport | |
| dc.subject.other | Cost Function | |
| dc.subject.other | Optimization Problem | |
| dc.subject.other | Nonlinear Model | |
| dc.subject.other | Prediction Horizon | |
| dc.subject.other | Input Constraints | |
| dc.subject.other | Path Tracking | |
| dc.subject.other | Suspended Load | |
| dc.subject.other | Multibody Model | |
| dc.subject.other | Thrust Force | |
| dc.subject.other | Inertial Frame | |
| dc.subject.other | Linear Matrix Inequalities | |
| dc.subject.other | Equations Of Motion | |
| dc.title | Model predictive control of a tilt-rotor UAV for load transportation | |
| dc.type | Artigo de evento | |
| local.citation.epage | 2170 | |
| local.citation.spage | 2165 | |
| local.description.resumo | In this paper a model predictive control (MPC) is used to solve the path tracking problem of a tilt-rotor unmanned aerial vehicle while it carries a suspended load. The MPC is designed based on the linear error model of the system, which is linearized around a generic trajectory. The control action is calculated via an optimization problem, where a cost function is solved taking into account input and state constraints. Furthermore, the MPC considers a terminal cost in order to ensure stability, allowing the prediction horizon reduction. The multibody non-linear dynamic model is obtained via Euler-Lagrange formulation, assuming four rigid bodies and ten degrees of freedom (DOF) of the vehicle. Numerical simulations are performed with the objective to evaluate the controller considering constant disturbances at different instants of time, and modeling errors. | |
| local.publisher.country | Brasil | |
| local.publisher.department | ENG - DEPARTAMENTO DE ENGENHARIA ELETRÔNICA | |
| local.publisher.initials | UFMG | |
| local.url.externa | https://ieeexplore.ieee.org/document/7810612 |
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