Simulation shows effective altitude transition in unmanned aerial vehicles using model predictive control, indicating improved aerodynamic management.
This study examines the altitude-hold flight mode transition problem for tail-sitter unmanned aerial vehicles (UAVs) between hovering and level flight. The problem is significantly challenging because of the complicated nonlinear aerodynamics of tail-sitter UAVs during the transition process. To address this problem, this article proposes a minimum snap trajectory generation method and a model predictive control (MPC)-based tracking strategy. First, the generated trajectories are highly applicable, satisfying the dynamic constraint. Second, MPC tracks full states by solving a finite-horizon optimization problem at each step, yielding the optimal future behavior based on the system model. A numerical simulation was conducted in which the altitude changed by less than 1.4 m during the entire transition process.
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Fan et al. (2025) studied this question.
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