  We demonstrate that direct data-driven control of nonlinear systems can be
successfully accomplished via a behavioral approach that builds on a Linear
Parameter-Varying (LPV) system concept. An LPV data-driven representation is
used as a surrogate LPV form of the data-driven representation of the original
nonlinear system. The LPV data-driven control design that builds on this
representation form uses only measurement data from the nonlinear system and a
priori information on a scheduling map that can lead to an LPV embedding of the
nonlinear system behavior. Efficiency of the proposed approach is demonstrated
experimentally on a nonlinear unbalanced disc system showing for the first time
in the literature that behavioral data-driven methods are capable to stabilize
arbitrary forced equilibria of a real-world nonlinear system by the use of only
7 data points.
