Physics-informed machine learning identifies a sparse control-affine model that is embedded in an adaptive tube MPC scheme for aerial vehicles, with stability proofs and demonstrated reductions in computation alongside improved tracking over baselines.
Xu, Reinforcement learning-based distributed optimal formation tracking control with obstacle avoidance for quadrotor UA Vs, Aerospace Science and Technology 173 (2026) 111789
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Physics-informed sparse identification-based tube model predictive control for aerial vehicles
Physics-informed machine learning identifies a sparse control-affine model that is embedded in an adaptive tube MPC scheme for aerial vehicles, with stability proofs and demonstrated reductions in computation alongside improved tracking over baselines.