  We describe a new temporal verification framework for safety and robustness
analysis of nonlinear control laws, our target application being a space
launcher vehicle. Robustness analysis, formulated as a nonconvex nonlinear
optimization problem on admissible trajectories corresponding to piecewise
polynomial dynamics, is relaxed into a convex linear programming problem on
measures. This infinite-dimensional problem is then formulated as a generalized
moment problem, which allows for a numerical solution via a hierarchy of linear
matrix inequality relaxations solved by semidefinite programming. The approach
is illustrated on space launcher vehicle benchmark problems, in the presence of
closed-loop nonlinearities (saturations and dead-zones) and axis coupling.
