微分平坦な固定翼航空システムの軌道追従のための非線形モデル予測制御
Nonlinear Model Predictive Control for Trajectory Tracking of Differentially Flat Fixed-Wing Aerial Systems
微分平坦性に基づく軌道生成と非線形モデル予測制御を統合し、風を考慮したサンプリング戦略を導入して、固定翼UAVの複雑な軌道追従精度とロバスト性を向上させた。
著者: Nishanth Bobbili, Pratyaksh Rao, Luca Morando, Luca Masci, Giuseppe Loianno
分類: cs.RO
原文アブストラクト
Planning and control of fixed-wing Unmanned Aerial Vehicles (UAVs) are challenging due to nonlinear dynamics, aerodynamic limits, and environmental disturbances. Differential flatness offers a principled way to generate fast, feasible trajectories, but its use has largely been confined to model-free controllers, which lack predictive capabilities and demand tuning. In this paper, we propose a unified framework that integrates differential flatness-based trajectory generation with Nonlinear Model Predictive Control (NMPC), combining computationally efficient planning with predictive, constraint-aware control. To further improve robustness, we introduce a wind-aware sampling strategy embedded within the NMPC framework, enabling the generation of dynamically feasible reference trajectories that proactively account for wind disturbances while strictly enforcing aerodynamic and control input constraints. We validate the proposed framework through extensive simulations and real-world flight experiments, demonstrating improved tracking accuracy and robustness for complex trajectories, particularly when using the proposed wind-aware sampling strategy under strong wind conditions.