Neural Koopman Control Barrier Functions for Safety-Critical Control of Unknown Nonlinear Systems
Author:
Affiliation:
1. The University of Texas at Austin,Department of Aerospace Engineering and Engineering Mechanics,Austin,Texas,USA,78712-1221
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10155646/10155787/10156243.pdf?arnumber=10156243
Reference33 articles.
1. Learning Control Barrier Functions from Expert Demonstrations
2. Proving the Correctness of Multiprocess Programs
3. Data-Driven Safety-Critical Control: Synthesizing Control Barrier Functions With Koopman Operators
4. Synthesis of Control Barrier Functions Using a Supervised Machine Learning Approach
5. δ-Complete Decision Procedures for Satisfiability over the Reals
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1. Disturbance Observer-Based Robust Integral Control Barrier Functions for Nonlinear Systems with High Relative Degree;2024 American Control Conference (ACC);2024-07-10
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