  We consider noisy input/state data collected from an experiment on a
polynomial input-affine nonlinear system. Motivated by event-triggered control,
we provide data-based conditions for input-to-state stability with respect to
measurement errors. Such conditions, which take into account all dynamics
consistent with data, lead to the design of a feedback controller, an ISS
Lyapunov function, and comparison functions ensuring ISS with respect to
measurement errors. When solved alternately for two subsets of the decision
variables, these conditions become a convex sum-of-squares program. Feasibility
of the program is illustrated with a numerical example.
