Secure-by-construction synthesis of cyber-physical systems
Correct-by-construction synthesis is a cornerstone of the confluence of formal methods and
control theory towards designing safety-critical systems. Instead of following the time-tested …
control theory towards designing safety-critical systems. Instead of following the time-tested …
Safe control with learned certificates: A survey of neural lyapunov, barrier, and contraction methods for robotics and control
Learning-enabled control systems have demonstrated impressive empirical performance on
challenging control problems in robotics, but this performance comes at the cost of reduced …
challenging control problems in robotics, but this performance comes at the cost of reduced …
Safe nonlinear control using robust neural lyapunov-barrier functions
Safety and stability are common requirements for robotic control systems; however,
designing safe, stable controllers remains difficult for nonlinear and uncertain models. We …
designing safe, stable controllers remains difficult for nonlinear and uncertain models. We …
Safe control with learned certificates: A survey of neural lyapunov, barrier, and contraction methods
Learning-enabled control systems have demonstrated impressive empirical performance on
challenging control problems in robotics, but this performance comes at the cost of reduced …
challenging control problems in robotics, but this performance comes at the cost of reduced …
FOSSIL: a software tool for the formal synthesis of lyapunov functions and barrier certificates using neural networks
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 …
and of barrier certificates (or functions) for dynamical systems modelled as differential …
Exact verification of relu neural control barrier functions
Abstract Control Barrier Functions (CBFs) are a popular approach for safe control of
nonlinear systems. In CBF-based control, the desired safety properties of the system are …
nonlinear systems. In CBF-based control, the desired safety properties of the system are …
Learning lyapunov functions for hybrid systems
We propose a sampling-based approach to learn Lyapunov functions for a class of discrete-
time autonomous hybrid systems that admit a mixed-integer representation. Such systems …
time autonomous hybrid systems that admit a mixed-integer representation. Such systems …
Physics-informed machine learning for modeling and control of dynamical systems
Physics-informed machine learning (PIML) is a set of methods and tools that systematically
integrate machine learning (ML) algorithms with physical constraints and abstract …
integrate machine learning (ML) algorithms with physical constraints and abstract …
Learning safe, generalizable perception-based hybrid control with certificates
C Dawson, B Lowenkamp, D Goff… - IEEE Robotics and …, 2022 - ieeexplore.ieee.org
Many robotic tasks require high-dimensional sensors such as cameras and Lidar to navigate
complex environments, but developing certifiably safe feedback controllers around these …
complex environments, but developing certifiably safe feedback controllers around these …
Compositional policy learning in stochastic control systems with formal guarantees
Reinforcement learning has shown promising results in learning neural network policies for
complicated control tasks. However, the lack of formal guarantees about the behavior of …
complicated control tasks. However, the lack of formal guarantees about the behavior of …