Simulation-based approaches for verification of embedded control systems: An overview of traditional and advanced modeling, testing, and verification techniques

J Kapinski, JV Deshmukh, X **, H Ito… - IEEE Control Systems …, 2016 - ieeexplore.ieee.org
Designers of industrial embedded control systems, such as automotive, aerospace, and
medical-device control systems, use verification and testing activities to increase their …

Safe control with learned certificates: A survey of neural lyapunov, barrier, and contraction methods for robotics and control

C Dawson, S Gao, C Fan - IEEE Transactions on Robotics, 2023 - ieeexplore.ieee.org
Learning-enabled control systems have demonstrated impressive empirical performance on
challenging control problems in robotics, but this performance comes at the cost of reduced …

Neural lyapunov control

YC Chang, N Roohi, S Gao - Advances in neural …, 2019 - proceedings.neurips.cc
We propose new methods for learning control policies and neural network Lyapunov
functions for nonlinear control problems, with provable guarantee of stability. The framework …

dReach: δ-Reachability Analysis for Hybrid Systems

S Kong, S Gao, W Chen, E Clarke - … for the Construction and Analysis of …, 2015 - Springer
Abstract dReach is a bounded reachability analysis tool for nonlinear hybrid systems. It
encodes reachability problems of hybrid systems to first-order formulas over real numbers …

[HTML][HTML] Review on computational methods for Lyapunov functions

P Giesl, S Hafstein - Discrete and Continuous Dynamical Systems …, 2015 - aimsciences.org
Lyapunov functions are an essential tool in the stability analysis of dynamical systems, both
in theory and applications. They provide sufficient conditions for the stability of equilibria or …

Safe control with learned certificates: A survey of neural lyapunov, barrier, and contraction methods

C Dawson, S Gao, C Fan - arxiv preprint arxiv:2202.11762, 2022 - arxiv.org
Learning-enabled control systems have demonstrated impressive empirical performance on
challenging control problems in robotics, but this performance comes at the cost of reduced …

Formal synthesis of Lyapunov neural networks

A Abate, D Ahmed, M Giacobbe… - IEEE Control Systems …, 2020 - ieeexplore.ieee.org
We propose an automatic and formally sound method for synthesising Lyapunov functions
for the asymptotic stability of autonomous non-linear systems. Traditional methods are either …

Learning certified control using contraction metric

D Sun, S Jha, C Fan - Conference on Robot Learning, 2021 - proceedings.mlr.press
In this paper, we solve the problem of finding a certified control policy that drives a robot from
any given initial state and under any bounded disturbance to the desired reference …

FOSSIL: a software tool for the formal synthesis of lyapunov functions and barrier certificates using neural networks

A Abate, D Ahmed, A Edwards, M Giacobbe… - Proceedings of the 24th …, 2021 - dl.acm.org
This paper accompanies FOSSIL: a software tool for the synthesis of Lyapunov functions
and of barrier certificates (or functions) for dynamical systems modelled as differential …

Design automation of cyber-physical systems: Challenges, advances, and opportunities

SA Seshia, S Hu, W Li, Q Zhu - IEEE Transactions on Computer …, 2016 - ieeexplore.ieee.org
A cyber-physical system (CPS) is an integration of computation with physical processes
whose behavior is defined by both computational and physical parts of the system. In this …