1 citations · 2 across the 5 of their papers we have counts for
5 papers
Distributed Control of Network Systems in the Space of Stabilizing Graph Neural Network Policies
John Cao, Luca Furieri
We study distributed control of networked systems through reinforcement learning, where neural policies must be simultaneously scalable, expressive and stabilizing. We introduce a…
KKL Observer Synthesis for Nonlinear Systems via Physics-Informed Learning
M. Umar B. Niazi, John Cao, Matthieu Barreau +1
This paper proposes a novel learning approach for designing Kazantzis-Kravaris or nonlinear Luenberger (KKL) observers for autonomous nonlinear systems. The design of a KKL observe…
ConvexECG: Lightweight and Explainable Neural Networks for Personalized, Continuous Cardiac Monitoring
Rayan Ansari, John Cao, Sabyasachi Bandyopadhyay +3
We present ConvexECG, an explainable and resource-efficient method for reconstructing six-lead electrocardiograms (ECG) from single-lead data, aimed at advancing personalized and c…
Sensor Fault Detection and Isolation in Autonomous Nonlinear Systems Using Neural Network-Based Observers
John Cao, Muhammad Umar B. Niazi, Matthieu Barreau +1
This paper presents a novel observer-based approach to detect and isolate faulty sensors in nonlinear systems. The proposed sensor fault detection and isolation (s-FDI) method appl…
Learning-based Design of Luenberger Observers for Autonomous Nonlinear Systems
Muhammad Umar B. Niazi, John Cao, Xudong Sun +2
Designing Luenberger observers for nonlinear systems involves the challenging task of transforming the state to an alternate coordinate system, possibly of higher dimensions, where…