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eess.SY2026
Integrating Deep Learning and Contraction Theory for Robust Nonlinear State Estimation via Unsupervised Scientific Machine Learning
Yasmine Marani, Israel Filho, Eric Feron +1
A common way to design observers is to add a correction term to a copy of the system; however, designing the correction term for nonlinear systems remains a significant long-standi…
eess.SY2024
Unsupervised Physics-Informed Neural Network-based Nonlinear Observer design for autonomous systems using contraction analysis
Yasmine Marani, Israel Filho, Tareq Al-Naffouri +1
Contraction analysis offers, through elegant mathematical developments, a unified way of designing observers for a general class of nonlinear systems, where the observer correction…
eess.SY2023
Non-Asymptotic State and Disturbance Estimation for a Class of Triangular Nonlinear Systems using Modulating Functions
Yasmine Marani, Ibrahima N'Doye, Taous-Meriem Laleg-Kirati
Dynamical models are often corrupted by model uncertainties, external disturbances, and measurement noise. These factors affect the performance of model-based observers and as a re…