Learning Neural Feedback Linearization for Data-driven Systems via Augmented Lagrangian

arXiv:2609.25163 · cs.LG · Submitted 2026-09-21 · Read on arXiv

cs.LG

Submitted: 2026-09-21

Updated: 2026-09-21

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• System Identification — 4× in this paper · explained in 3 episodes
• Activation Function — 3× in this paper · explained in 1 episode
• Consistency — 3× in this paper · explained in 3 episodes
• Robustness — 3× in this paper · explained in 5 episodes
• Closed-Loop System — 2× in this paper · explained in 4 episodes
• Loss Function — 2× in this paper · explained in 2 episodes
• Reinforcement Learning — 2× in this paper · explained in 4 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Decoupling — 1× in this paper · explained in 2 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Verification — 1× in this paper · explained in 2 episodes

Sources

• Data-driven Stabilization of SISO Feedback Linearizable Systems
• A Taxonomy of Numerical Differentiation Methods
• Data driven feedback linearization of nonlinear control systems via Lie derivatives and stacked regression approach
• Identification For Control Based on Neural Networks: Approximately Linearizable Models

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