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.
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