Data-driven approximation of regions of attraction via an LP-based selection of PWA Lyapunov functions
The research develops a method to estimate regions of attraction for unknown nonlinear systems using data. It constructs continuous piecewise affine (PWA) Lyapunov functions by selecting partition vertices based on an LP optimization process. This allows for certifying a safe region around an equilibrium even when the system model is not explicitly known.