Year: 2025
Type: article
Abstract: Trajectory planning for fixed-wing unmanned aerial vehicles (UAVs) requires time optimality under complex dynamic and physical constraints, which is critical for task efficiency. To address the high complexity and inaccurate constraint satisfaction of traditional methods in variable time domains and limited states of UAVs, this study proposes an approach integrating control parameterization and exact penalty function. Continuous controls of the commonly used three-degree-of-freedom (3-DOF) dynamic model are converted to finite parameters, and time optimality is considered as the optimization objective. Furthermore, state and control constraints of UAVs are embedded into the objective function via a dynamic penalty parameter. To enable the actual state of the six-degree-of-freedom (6-DOF) UAV model to track the planned trajectory, we impose multiple state and control constraints and conduct re-planning within the framework of model predictive control. Experiments on the F-16 aircraft model verify the method's feasibility and effectiveness.
Authors: Yangzhou Cao, Bin Li
Institution: Sichuan University
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
Award: G2647115387
OpenAlex ID: W7115924928