A version of SANE was used to evolve feedback controllers for chaotic systems. Standard methods for this task require an analytical description of the system near the fixed point. In contrast, the SANE networks were able to stabilize unstable fixed points for logistic and Henon maps under noise, and without prior knowledge of the system such as the location of the points or the dimensionality of the system. Such robustness suggests that the method could scale up well to real-world applications.