Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/81916
Title: Nonlinear automatic landing control of unmanned aerial vehicles on moving platforms via a 3D laser radar
Authors: Hervas, Jaime Rubio
Reyhanoglu, Mahmut
Tang, Hui
Keywords: UAV
Sliding mode
Nonlinear control
State estimation
Extended Kalman filter
Laser radar
Landing
Issue Date: 2014
Source: Hervas, J. R., Reyhanoglu, M., & Tang, H. (2014). Nonlinear automatic landing control of unmanned aerial vehicles on moving platforms via a 3D laser radar. AIP Conference Proceedings, 907-917.
Abstract: This paper presents a motion tracking and control system for automatically landing Unmanned Aerial Vehicles (UAVs) on an oscillating platform using Laser Radar (LADAR) observations. The system itself is assumed to be mounted on a ship deck. A full nonlinear mathematical model is first introduced for the UAV. The ship motion is characterized by a Fourier transform based method which includes a realistic characterization of the sea waves. LADAR observation models are introduced and an algorithm to process those observations for yielding the relative state between the vessel and the UAV is presented, from which the UAV's state relative to an inertial frame can be obtained and used for feedback purposes. A sliding mode control algorithm is derived for tracking a landing trajectory defined by a set of desired waypoints. An extended Kalman filter (EKF) is proposed to account for process and observation noises in the design of a state estimator. The effectiveness of the control algorithm is illustrated through a simulation example.
URI: https://hdl.handle.net/10356/81916
http://hdl.handle.net/10220/39711
DOI: 10.1063/1.4904663
Rights: © 2014 American Institute of Physics. This paper was published in AIP Conference Proceedings and is made available as an electronic reprint (preprint) with permission of American Institute of Physics. The published version is available at: [http://dx.doi.org/10.1063/1.4904663]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Conference Papers

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