  We propose a data-driven control design method for nonlinear systems that
builds on kernel-based interpolation. Under some assumptions on the system
dynamics, kernel-based functions are built from data and a model of the system,
along with deterministic model error bounds, is determined. Then, we derive a
controller design method that aims at stabilizing the closed-loop system by
cancelling out the system nonlinearities. The proposed method can be
implemented using semidefinite programming and returns positively invariant
sets for the closed-loop system.
