  In this paper, we directly design a state feedback controller that stabilizes
a class of uncertain nonlinear systems solely based on input-state data
collected from a finite-length experiment. Necessary and sufficient conditions
are derived to guarantee that the system is absolutely stabilizable and a
controller is designed. Results derived under some relaxed prior information
about the system and strengthened data assumptions are also discussed.
Numerical examples illustrate the method with different levels of prior
information.
