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Flight control of very flexible unmanned aerial vehicles
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Qi, Pengyuan (2019) Flight control of very flexible unmanned aerial vehicles. PhD thesis, University of Warwick.
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WRAP_Theses_Qi_2019.pdf - Submitted Version - Requires a PDF viewer. Download (13Mb) | Preview |
Official URL: http://webcat.warwick.ac.uk/record=b3684455
Abstract
This thesis aims to investigate the flight control of a very flexible ying wing model already developed in the literature. The model was derived from geometrically nonlinear beam theory using intrinsic degrees of freedom and linear unsteady aerodynamics, which resulted in a coupled structural dynamics, aerodynamics, and flight dynamics description. The scenarios of trajectory tracking and autonomous landing in the presence of wind disturbance are considered in control designs.
Firstly, the aeroelastic and trajectory control of this very flexible ying wing model is studied. The control design employs a two-loop PI/LADRC (proportional integral/linear active disturbance rejection control) and H1 control scheme, based on a reduced-order linear model. The outer loop employs the PI/LADRC technique to track the desired flight paths and generate attitude commands to the inner loop, while the inner loop uses H1 control to track the attitude command and computes the corresponding control inputs. The particle swarm optimization algorithm is employed for parameter optimization in the H1 control design to enhance the control effectiveness and robustness. Simulation tests conducted on the full-order nonlinear model show that the designed aeroelastic and trajectory control system achieves good performance in aspects of tracking effectiveness and robustness against disturbance rejection.
Secondly, the preview-based autonomous landing control of the very flexible ying wing model using light detection and ranging (Lidar) wind measurements is studied. The preview control system follows the above two-loop control structure and is also designed based on the reduced-order linear model. The outer loop emxv ploys the same LADRC and PI algorithms to track the reference landing trajectory and vertical speed, respectively. But the inner loop is extended to introduce Lidar wind measurements at a distance in front of the aircraft, employing H1 preview control to improve disturbance rejection performance during landing. Simulation results based on the full-order nonlinear model show that the preview-based landing control system is able to land the aircraft safely and effectively, which also achieves better control performance than a baseline landing control system (without preview) with respect to landing effectiveness and disturbance rejection.
Finally, the data-driven flight control of the very flexible ying wing model using Model-Free Adaptive Control (MFAC) scheme to reduce the dependence of control design on system modeling is studied. A cascaded proportional-derivative MFAC (PD-MFAC) approach is proposed to accommodate the MFAC scheme in a flight control problem, which shows better control performance over the original MFAC algorithm. Based on the PD-MFAC approach, the data-driven flight control system is developed to achieve gust load alleviation and trajectory tracking. Simulation results based on the full-order nonlinear model show that the proposed data-driven flight control system is able to properly regulate all the rigid-body and flexible modes with better effectiveness and robustness (against disturbance rejection and modeling uncertainties), compared to a baseline H1 flight control system.
Item Type: | Thesis (PhD) | ||||
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Subjects: | T Technology > TL Motor vehicles. Aeronautics. Astronautics | ||||
Library of Congress Subject Headings (LCSH): | Drone aircraft -- Control systems, Flight control, Aeroelasticity, Landing aids (Aeronautics), Airplanes -- Design and construction, Trajectory optimization | ||||
Official Date: | December 2019 | ||||
Dates: |
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Institution: | University of Warwick | ||||
Theses Department: | School of Engineering | ||||
Thesis Type: | PhD | ||||
Publication Status: | Unpublished | ||||
Supervisor(s)/Advisor: | Zhao, Xiaowei | ||||
Format of File: | |||||
Extent: | xix, 143 leaves : illustrations | ||||
Language: | eng |
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