A qLMPC Framework for Path-Following Control of Fixed-Wing UAVs
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Beschreibung
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.
Autor*in
Ahmed Samir Rezk