Data-driven prediction and control for NARX systems

We consider two problems related to control of unknown nonlinear systems: find the input which generates a given trajectory and tracking a given trajectory from a predicted one. The proposed method predicts the system future evolution directly from the available data, hence without estimating a system plant. While data-driven control problem are known and studied for linear systems, only special classes of systems are considered in the literature for the nonlinear case.