A new robust adaptive mixing control for trajectory tracking with improved forward flight of a tilt-rotor UAV

A new robust adaptive mixing control (RAMC) is proposed in order to accomplish trajectory tracking of a tilt-rotor unmanned aerial vehicle (UAV) configuration. This kind of system is a hybrid aerial vehicle that combines advantages of rotary-wing aircraft, like hovering flight and vertical take-off...

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Detalles Bibliográficos
Autores: Cardoso, Daniel N., Esteban Roncero, Sergio, Raffo, Guilherme V.
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2021
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/167461
Acceso en línea:https://hdl.handle.net/11441/167461
https://doi.org/10.1016/j.isatra.2020.10.040
Access Level:acceso abierto
Palabra clave:Convertible UAV
Tilt-rotor
Adaptive mixing control
Robust control
Descripción
Sumario:A new robust adaptive mixing control (RAMC) is proposed in order to accomplish trajectory tracking of a tilt-rotor unmanned aerial vehicle (UAV) configuration. This kind of system is a hybrid aerial vehicle that combines advantages of rotary-wing aircraft, like hovering flight and vertical take-off and landing (VTOL), and those of fixed-wing aircraft, as improved forward flight. Although the VTOL and cruise flight regimes present different dynamic behaviors, in this work a unified, highly coupled, nonlinear model is developed to cope with the considered tilt-rotor UAV full flight envelope, that is, the axial flight, hovering, transition/cruise and turning flight. The modeling is performed via Euler–Lagrange formulation considering the tilt-rotor UAV as a multi-body system and taking into account aerodynamic effects and the dynamics of the tilting servomotors. Accordingly, in order to comply with the trajectory tracking requirements and improve the tilt-rotor UAV forward flight, this paper presents a novel robust adaptive mixing controller which is formulated to deal with linear parameter-varying (LPV) systems dependent on not known a priori large parameters but measured or estimated online, and also to provide robustness against unknown disturbances. Additionally, a rigorous closed-loop stability analysis is performed. The controller performance is validated with numerical experiments conducted using a high fidelity simulator developed on Gazebo and Robot Operating System (ROS) platforms.