同定した制御拡張ダイナミクスを用いた固定翼UAVの非線形モデル予測誘導
Nonlinear Model Predictive Guidance for Fixed-wing UAVs Using Identified Control Augmented Dynamics
市販オートパイロット搭載の小型固定翼機について制御拡張ダイナミクスをモデル同定し、それに基づく非線形モデル予測制御で対気速度安定化と経路追従を両立させ、強風下やモータ故障時を含む飛行実験で検証した。
著者: Thomas Stastny, Roland Siegwart
分類: cs.RO
原文アブストラクト
As off-the-shelf (OTS) autopilots become more widely available and user-friendly and the drone market expands, safer, more efficient, and more complex motion planning and control will become necessary for fixed-wing aerial robotic platforms. Considering typical low-level attitude stabilization available on OTS flight controllers, this paper first develops an approach for modeling and identification of the control augmented dynamics for a small fixed-wing Unmanned Aerial Vehicle (UAV). A high-level Nonlinear Model Predictive Controller (NMPC) is subsequently formulated for simultaneous airspeed stabilization, path following, and soft constraint handling, using the identified model for horizon propagation. The approach is explored in several exemplary flight experiments including path following of helix and connected Dubins Aircraft segments in high winds as well as a motor failure scenario. The cost function, insights on its weighting, and additional soft constraints used throughout the experimentation are discussed.
関連論文
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