4 papers
Late Fusion Neural Operators for Extrapolation Across Parameter Space in Partial Differential Equations
Eva van Tegelen, Taniya Kapoor, George A. K. van Voorn +2
Developing neural operators that accurately predict the behavior of systems governed by partial differential equations (PDEs) across unseen parameter regimes is crucial for robust…
Neural Ordinary Differential Equations for Learning and Extrapolating System Dynamics Across Bifurcations
Eva van Tegelen, George van Voorn, Ioannis Athanasiadis +1
Forecasting system behaviour near and across bifurcations is crucial for identifying potential shifts in dynamical systems. While machine learning has recently been used to learn c…
Partial Eigenvalue Assignment for Nonlinear Systems
Shang Wang, Xiaodong Cheng, Yu Kawano +1
In this paper, we study control design methods for assigning a subset of nonlinear right or left eigenvalues to a specified set of scalar-valued functions via nonlinear Sylvester e…
A Distributed Time-Varying Optimization Approach Based on an Event-Triggered Scheme
Haojin Li, Xiaodong Cheng, Peter van Heijster +1
In this paper, we present an event-triggered distributed optimization approach including a distributed controller to solve a class of distributed time-varying optimization problems…