Neural Architectures as Functional Priors in Physics-Informed Control Problems
In this work we investigate the role of neural architectures as implicit functional priors in control problems governed by ordinary differential equations. Rather than focusing on highly complex problems, our objective is to investigate architecture-dependent effects in controlled dynamical systems within the simplest physically interpretable settings possible. In particular, we study a controlled linear RLC electrical circuit and a nonlinear Duffing-type dynamical system. Both systems are analyzed first through classical optimal-control formulations and later through PINN-based approaches. We compare different combinations of multilayer perceptrons (MLPs) and Fourier-based KAN-like archi...
| Authors | Sonia Rubio Herranz, Fernando Carlos López Hernández, Antonio López Montes |
|---|---|
| Primary category | math.NA |
| Published | 11 June 2026 |
| Last updated at source | 11 June 2026 |
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