TS10: Physics-Informed Control
Technical Session 10 — Control Theory and Methods.
Papers
| Time | Title | Authors |
|---|---|---|
| 15:20–15:40 | Physics-Informed Learning of 3-DoF Helicopter Dynamics via Lagrangian Neural Networks and Simulation Data | Oscar Navas; Juan Navas; Carlos Borrás |
| 15:40–16:00 | Neural Network Nonlinear Identification based on parameterized FEM PMSM Model | Sergio Velarde-Gomez; Eduardo Giraldo |
| 16:00–16:20 | Robust Input-State Feedback Linearization Using Physics-Informed Neural Networks | Camilo E. Zambrano; Eduardo Mojica-Nava |
| 16:20–16:40 | Solving Fluid and Diffusion Dynamics Problems using Physics-Informed Neural Networks and the Lattice Boltzmann Method | Cristian Esteban Peña Velandia; Eduardo Mojica-Nava |
| 16:40–17:00 | Constrained Model Predictive Control and LQR with Integral Action for a Rotary Inverted Pendulum | Jose Quintana and Yineth Martinez Armero |