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A qLMPC framework for path-following control of fixed-wing UAVs
Citation Link: https://doi.org/10.15480/882.15318
Publikationstyp
Doctoral Thesis
Date Issued
2025
Sprache
English
Author(s)
Advisor
Referee
Title Granting Institution
Technische Universität Hamburg
Place of Title Granting Institution
Hamburg
Examination Date
2024-06-17
Institute
TORE-DOI
Citation
Technische Universität Hamburg (2025)
ISBN
978-3-8439-5621-5
This thesis presents a novel predictive path-following control scheme for fixed-wing UAVs, addressing limitations in the existing literature. While geometric methods struggle with variable winds and predictive strategies tend to be computationally intensive, the qLPV approach proposed here strikes a balance—accurately capturing the system dynamics while maintaining computational efficiency through the use of Quadratic Programs (QPs). The practicability of the approach is demonstrated by applying it to a high-fidelity model of the ULTRA-Extra UAV. Constructing qLPV representations is not unique; in this work, velocity-based linearization is employed, which is known to be well-suited for controller design. It is also compatible with offset-free Model Predictive Control (MPC) and enables efficient disturbance rejection. The proposed framework is further extended to obstacle avoidance by representing obstacles as qLPV constraints.
Subjects
Path-Following
Control Systems
qLMPC
Obstacle Avoidance
Stability Analysis
Fixed-Wing UAVs
DDC Class
629.13: Aviation Engineering
629.89: Computer-Controlled Guidance
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Diss_AS.pdf
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Format
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