Data-Driven Saturated State Feedback Design for Polynomial Systems Using Noisy Data

In this note, the problem of data-driven saturated state feedback design for polynomial nonlinear systems is solved by means of a sum-of-squares (SOS) approach. This new strategy combines recent results in dissipativity theory and data-driven feedback control using noisy input-state data. SOS optimization is employed in this work for controller design and to deliver an estimate of the closed-loop domain of attraction under saturated feedback. Numerical examples allow the reader to verify the usefulness of our strategy, which is the first in literature to provide a datadriven and dissipativity-based approach for solving the problem of input saturation for continuous-time polynomial systems.