LoL-NMPC: 無人航空機のための非線形モデル予測制御における低レベルダイナミクス統合
LoL-NMPC: Low-Level Dynamics Integration in Nonlinear Model Predictive Control for Unmanned Aerial Vehicles
UAVの高速機敏な軌道追従において、低レベルのPID制御器やモータのダイナミクスをNMPCに明示的に組み込むことで、追従誤差を平均21.97%削減し、98.57 km/h・3.5gでもリアルタイム(100Hz)動作を実現した。
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著者: Parakh M. Gupta, Ondřej Procházka, Jan Hřebec, Matej Novosad, Robert Pěnička, Martin Saska
分類: cs.RO
原文アブストラクト
[Accepted to IROS 2025] In this paper, we address the problem of tracking high-speed agile trajectories for Unmanned Aerial Vehicles(UAVs), where model inaccuracies can lead to large tracking errors. Existing Nonlinear Model Predictive Controller(NMPC) methods typically neglect the dynamics of the low-level flight controllers such as underlying PID controller present in many flight stacks, and this results in sub-optimal tracking performance at high speeds and accelerations. To this end, we propose a novel NMPC formulation, LoL-NMPC, which explicitly incorporates low-level controller dynamics and motor dynamics in order to minimize trajectory tracking errors while maintaining computational efficiency. By leveraging linear constraints inside low-level dynamics, our approach inherently accounts for actuator constraints without requiring additional reallocation strategies. The proposed method is validated in both simulation and real-world experiments, demonstrating improved tracking accuracy and robustness at speeds up to 98.57 km/h and accelerations of 3.5 g. Our results show an average 21.97 % reduction in trajectory tracking error over standard NMPC formulation, with LoL-NMPC maintaining real-time feasibility at 100 Hz on an embedded ARM-based flight computer.
