Modern autonomous systems, such as flying, legged, and wheeled robots, are generally
characterized by high-dimensional nonlinear dynamics, which presents challenges for …

This tutorial paper presents recent work of the authors that extends the theory of Control
Barrier Functions (CBFs) to address practical challenges in the synthesis of safe controllers …

Today's control engineering problems exhibit an unprecedented complexity, with examples
including the reliable integration of renewable energy sources into power grids, safe …

This survey provides a brief overview on the control Lyapunov function (CLF) and control
barrier function (CBF) for general nonlinear-affine control systems. The problem of control is …

Control Barrier Functions (CBFs) and Control Lyapunov Functions (CLFs) are popular tools
for enforcing safety and stability of a controlled system, respectively. They are commonly …

This article focuses on the problem of adaptive safe stabilization for a class of nonlinear
control affine systems with parameter uncertainties. Two novel definitions of adaptive control …

Reinforcement Learning (RL) has been shown to be effective in many scenarios. However, it
typically requires the exploration of a sufficiently large number of state-action pairs, some of …

This paper studies the problem of utilizing data-driven adaptive control techniques to
guarantee stability and safety of uncertain nonlinear systems with high relative degree. We …

Learning-based control approaches have shown great promise in performing complex tasks
directly from high-dimensional perception data for real robotic systems. Nonetheless, the …

Symbolic models or abstractions are known to be powerful tools for the control design of
cyber–physical systems (CPSs) with logic specifications. In this paper, we investigate a …