34 citations · 77 across the 14 of their papers we have counts for
14 papers
Under-Approximate Reachability Analysis for a Class of Linear Systems with Inputs
Mohamed Serry, Jun Liu
Under-approximations of reachable sets and tubes have been receiving growing research attention due to their important roles in control synthesis and verification. Available under-…
Learning Control Barrier Functions with High Relative Degree for Safety-Critical Control
Chuanzheng Wang, Yinan Li, Yiming Meng +2
Control barrier functions have shown great success in addressing control problems with safety guarantees. These methods usually find the next safe control input by solving an onlin…
Structured Online Learning-based Control of Continuous-time Nonlinear Systems
Milad Farsi, Jun Liu
Model-based reinforcement learning techniques accelerate the learning task by employing a transition model to make predictions. In this paper, a model-based learning approach is pr…
Smooth Converse Lyapunov-Barrier Theorems for Asymptotic Stability with Safety Constraints and Reach-Avoid-Stay Specifications
Yiming Meng, Yinan Li, Maxwell Fitzsimmons +1
Stability and safety are two important aspects in safety-critical control of dynamical systems. It has been a well established fact in control theory that stability properties can…
Converse Barrier Functions via Lyapunov Functions
Jun Liu
We prove a robust converse barrier function theorem via the converse Lyapunov theory. While the use of a Lyapunov function as a barrier function is straightforward, the existence o…
On the Convergence of Reinforcement Learning with Monte Carlo Exploring Starts
Jun Liu
A basic simulation-based reinforcement learning algorithm is the Monte Carlo Exploring States (MCES) method, also known as optimistic policy iteration, in which the value function…