1 citations · 1 across the 15 of their papers we have counts for
8 papers · 1 filter
Event-Triggered Adaptive Taylor-Lagrange Control for Safety-Critical Systems
Shuo Liu, Wei Xiao, Christos G. Cassandras +1
This paper studies safety-critical control for nonlinear systems under sampled-data implementations of the controller. The recently proposed Taylor--Lagrange Control (TLC) method p…
Koopman-Based Linear MPC for Safe Control using Control Barrier Functions
Shuo Liu, Liang Wu, Dawei Zhang +2
This paper proposes a Koopman-based linear model predictive control (LMPC) framework for safety-critical control of nonlinear discrete-time systems. Existing MPC formulations based…
Feasibility-aware Learning of Robust Temporal Logic Controllers using BarrierNet
Wenliang Liu, Shuo Liu, Wei Xiao +1
Control Barrier Functions (CBFs) have been used to enforce safety and task specifications expressed in Signal Temporal Logic (STL). However, existing CBF-STL approaches typically r…
Sampling-Aware Control Barrier Functions for Safety-Critical and Finite-Time Constrained Control
Shuo Liu, Wei Xiao, Calin A. Belta
In safety-critical control systems, ensuring both safety and feasibility under sampled-data implementations is crucial for practical deployment. Existing Control Barrier Function (…
A Predictive and Sampled-Data Barrier Method for Safe and Efficient Quadrotor Control
Ming Gao, Zhanglin Shangguan, Shuo Liu +3
This paper proposes a cascaded control framework for quadrotor trajectory tracking with formal safety guarantees. First, we design a controller consisting of an outer-loop position…
Auxiliary-Variable Adaptive Control Barrier Functions
Shuo Liu, Wei Xiao, Calin A. Belta
This paper addresses the challenge of ensuring safety and feasibility in control systems using Control Barrier Functions (CBFs). Existing CBF-based Quadratic Programs (CBF-QPs) oft…
Safety-Critical Control with Guaranteed Lipschitz Continuity via Filtered Control Barrier Functions
Shuo Liu, Wei Xiao, Calin A. Belta
In safety-critical control systems, ensuring both system safety and smooth control input is essential for practical deployment. Existing Control Barrier Function (CBF) frameworks,…
Learning-Enabled Iterative Convex Optimization for Safety-Critical Model Predictive Control
Shuo Liu, Zhe Huang, Jun Zeng +2
Safety remains a central challenge in control of dynamical systems, particularly when the boundaries of unsafe sets are complex (e.g., nonconvex, nonsmooth) or unknown. This paper…