2 citations · 3 across the 2 of their papers we have counts for
2 papers
eess.SY2023★ 2 cited
Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems
Truong X. Nghiem, Ján Drgoňa, Colin Jones +10
Physics-informed machine learning (PIML) is a set of methods and tools that systematically integrate machine learning (ML) algorithms with physical constraints and abstract mathema…
eess.SY2022★ 1 cited
A Robust, Multiple Control Barrier Function Framework for Input Constrained Systems
Wenceslao Shaw Cortez, Xiao Tan, Dimos V. Dimarogonas
We propose a novel (Type-II) zeroing control barrier function (ZCBF) for safety-critical control, which generalizes the original ZCBF approach. Our method allows for applications t…