Fast Learning Digital Twin with Reduced Dimensionality for Non-linear Dynamical Systems

A black-box model of a nonlinear system can be obtained by observing the input-output pairs. We propose a reduced complexity modeling technique that, in many cases, represents the system sufficiently well for control applications. A real-time experimental setup based on an STM32 board is realized to model a nonlinear system and results are presented.