Fig. 1: Schematic illustration of our method.
From: Suppressing unknown disturbances to dynamical systems using machine learning
In the training phase (top row), a nonlinear system is forced with a training function f(t). Observations of the forced system are used to train a reservoir to approximate the training function, utrain(t). The reservoir subsequently identifies unknown disturbance function g(t) with an approximate disturbance function u(t) (bottom row).
