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On the Optimality, Stability, and Feasibility of Control Barrier
  Functions: An Adaptive Learning-Based Approach

On the Optimality, Stability, and Feasibility of Control Barrier Functions: An Adaptive Learning-Based Approach

5 May 2023
A. Chriat
Chuangchuang Sun
ArXivPDFHTML

Papers citing "On the Optimality, Stability, and Feasibility of Control Barrier Functions: An Adaptive Learning-Based Approach"

3 / 3 papers shown
Title
Learning-Enhanced Safeguard Control for High-Relative-Degree Systems: Robust Optimization under Disturbances and Faults
Xinyang Wang
Hongwei Zhang
Shimin Wang
Wei Xiao
M. Guay
51
0
0
28 Jan 2025
Distributionally Safe Reinforcement Learning under Model Uncertainty: A
  Single-Level Approach by Differentiable Convex Programming
Distributionally Safe Reinforcement Learning under Model Uncertainty: A Single-Level Approach by Differentiable Convex Programming
A. Chriat
Chuangchuang Sun
16
1
0
03 Oct 2023
A Theoretical Overview of Neural Contraction Metrics for Learning-based
  Control with Guaranteed Stability
A Theoretical Overview of Neural Contraction Metrics for Learning-based Control with Guaranteed Stability
Hiroyasu Tsukamoto
Soon-Jo Chung
Jean-Jacques E. Slotine
Chuchu Fan
16
10
0
02 Oct 2021
1