WSINDYc-MPC identifies governing dynamics more robustly than benchmarks under high noise, enabling longer prediction horizons and lower tracking errors in fusion, drone, chaos, and aircraft control tasks.
202 5 SINDy and PD-Based UA V Dynamics Identification for MPC
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WSINDy for Model Predictive Control with Applications to Fusion, Drones, and Chaos
WSINDYc-MPC identifies governing dynamics more robustly than benchmarks under high noise, enabling longer prediction horizons and lower tracking errors in fusion, drone, chaos, and aircraft control tasks.