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Neural-ESO: A Dual-Pathway Architecture for Provably Robust Learning-Based Control
A learning enabled disturbance rejection framework based on a Neural Extended State Observer (Neural ESO) is presented in this letter. Unlike existing learning based control methods that largely rely on the learned model once deployed, Neural ESO adopts a dual pathway architecture: a predictive pathway uses a neural network to provide a feedforward disturbance estimate that accelerates convergence, while a correct...