Revisiting PGD Attacks for Stability Analysis of Large-Scale Nonlinear Systems and Perception-Based Control. (arXiv:2201.00801v1 [math.OC])

Many existing region-of-attraction (ROA) analysis tools find difficulty in
addressing feedback systems with large-scale neural network (NN) policies
and/or high-dimensional sensing modalities such as cameras. In this paper, we
tailor the projected gradient descent (PGD) attack method developed in the
adversarial learning community as a general-purpose ROA analysis tool for
large-scale nonlinear systems and end-to-end perception-based control. We show
that the ROA analysis can be approximated as a constrained maximization problem
whose goal is to find the worst-case initial condition …

analysis arxiv attacks math perception systems