# Real-Time Disturbance-Aware Koopman Model Predictive Control for Quadrotors in Spatially Varying Winds

- Source: arXiv cs.RO
- Published: 2026-10-21T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/p4qk66iozt8y2o2mxmr986an8
- Original: https://arxiv.org/abs/2610.27414

## Summary

The study proposes a disturbance-aware Koopman control family (DA-KCF) framework that preserves an offline-identified nominal model, learns only a disturbance correction online, and embeds it into model predictive control (MPC) to optimize position and yaw references. The reference-dependent KCF is first learned from simulation data and then calibrated with limited hardware data; during deployment the nominal model remains fixed, and a lightweight residual ensemble learns a low-dimensional disturbance correction from causal state-command-state transitions.