Author

Feng-Jun Yang

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Preprint Sep 2026

Physics-Informed Learning of Feedback-Linearizing Representations

This work proposes a cascaded physics-informed neural network (PINN) framework to approximately solve partial differential equations (PDEs) and demonstrates that this approach can computationally discover effective feedback-linearizing representations of nonlinear systems for control tasks.

Pavlos Kallinikidis, Feng-Jun Yang, David Snyder et al. · 0 citations