arXiv · 2504.11125
A mixed-integer framework for analyzing neural network-based controllers for piecewise affine systems with bounded disturbances
Abstract
We present a method for representing the closed-loop dynamics of piecewise affine (PWA) systems with bounded additive disturbances and neural network-based controllers as mixed-integer (MI) linear constraints. We show that such representations enable the computation of robustly positively invariant (RPI) sets for the specified system class by solving MI linear programs. These RPI sets can subsequently be used to certify stability and constraint satisfaction. Furthermore, the approach allows to handle non-linear systems based on suitable PWA approximations and corresponding error bounds, which can be interpreted as the bounded disturbances from above.
Explore related subjects
Keep this discovery
Explore connections, maps & timelines
Dieter Teichrib, Moritz Schulze Darup. 2025-04-15. A mixed-integer framework for analyzing neural network-based controllers for piecewise affine systems with bounded disturbances. https://doi.org/10.23919/ecc65951.2025.11187202
Cite the original work for its findings. Save a collection to share your selection of sources.