20 citations · 67 across the 24 of their papers we have counts for
9 papers · 1 filter
Data-driven balanced truncation for linear systems with quadratic outputs
Reetish Padhi, Ion Victor Gosea, Igor Pontes Duff +1
We develop the framework for a non-intrusive, quadrature-based method for approximate balanced truncation (QuadBT) of linear systems with quadratic outputs, thus extending the appl…
Inference of Substructured Reduced-Order Models for Dynamic Contact from Contact-free Simulations
Diana Manvelyan-Stroot, Yevgeniya Filanova, Igor Pontes Duff +2
In this paper, we propose an operator-inference-based reduction approach for contact problems, leveraging snapshots from simulations without active contact. Contact problems are so…
-optimal model reduction of linear quadratic-output systems by multivariate rational interpolation
Sean Reiter, Ion Victor Gosea, Igor Pontes Duff +1
This paper addresses the -optimal approximation of linear dynamical systems with quadratic-output functions, also known as linear quadratic-output systems. Our major…
On the representation of energy-preserving quadratic operators with application to Operator Inference
Leonidas Gkimisis, Igor Pontes Duff, Pawan Goyal +1
In this work, we investigate a skew-symmetric parameterization for energy-preserving quadratic operators. Earlier, [Goyal et al., 2023] proposed this parameterization to enforce en…
optimal model reduction of linear systems with multiple quadratic outputs
Sean Reiter, Igor Pontes Duff, Ion Victor Gosea +1
In this work, we consider the optimal model reduction of dynamical systems that are linear in the state equation and up to quadratic nonlinearity in the output equation. As o…
Model order reduction for bilinear systems with non-zero initial states -- different approaches with error bounds
Martin Redmann, Igor Pontes Duff
In this paper, we consider model order reduction for bilinear systems with non-zero initial conditions. We discuss choices of Gramians for both the homogeneous and the inhomogeneou…
Full state approximation by Galerkin projection reduced order models for stochastic and bilinear systems
Martin Redmann, Igor Pontes Duff
In this paper, the problem of full state approximation by model reduction is studied for stochastic and bilinear systems. Our proposed approach relies on identifying the dominant s…
Toward fitting structured nonlinear systems by means of dynamic mode decomposition
Ion Victor Gosea, Igor Pontes Duff
The dynamic mode decomposition (DMD) is a data-driven method used for identifying the dynamics of complex nonlinear systems. It extracts important characteristics of the underlying…
Identification of Dominant Subspaces for Linear Structured Parametric Systems and Model Reduction
Peter Benner, Pawan Goyal, Igor Pontes Duff
In this paper, we discuss a novel model reduction framework for generalized linear systems. The transfer functions of these systems are assumed to have a special structure, e.g., c…