  Numerous interesting properties in nonlinear systems analysis can be written
as polynomial optimization problems with nonconvex sum-of-squares problems. To
solve those problems efficiently, we propose a sequential approach of local
linearizations leading to tractable, convex sum-of-squares problems. Local
convergence is proven under the assumption of strong regularity and the new
approach is applied to estimate the region of attraction of a polynomial
aircraft model.
