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Designing a static state-feedback controller subject to structural constraint achieving asymptotic stability is a relevant problem with many applications, including network decentralized control, coordinated control, and sparse feedback…

Optimization and Control · Mathematics 2021-06-03 Francesco Ferrante , Fabrizio Dabbene , Chiara Ravazzi

Reduced-order models (ROMs) that capture changes in fluid systems due to variations in parameters, such as the Reynolds number or the shape of a stationary body placed in the flow, are attracting increasing attention in engineering…

Fluid Dynamics · Physics 2025-12-16 Yuto Nakamura , Shintaro Sato , Naofumi Ohnishi

We develop a Reduced Order Model (ROM) for a Large Eddy Simulation (LES) approach that combines a three-step algorithm called Evolve-Filter-Relax (EFR) with a computationally efficient finite volume method. The main novelty of our ROM lies…

Numerical Analysis · Mathematics 2021-07-28 Michele Girfoglio , Annalisa Quaini , Gianluigi Rozza

Model order reduction through the POD-Galerkin method can lead to dramatic gains in terms of computational efficiency in solving physical problems. However, the applicability of the method to non linear high-dimensional dynamical systems…

This paper discusses the boundary feedback stabilization of a reaction-diffusion equation with Robin boundary conditions and in the presence of a time-varying state-delay. The proposed control design strategy is based on a…

Optimization and Control · Mathematics 2020-03-17 Hugo Lhachemi , Robert Shorten

Model order reduction (MOR) is an important step in the design process of integrated circuits. Specifically, the electromagnetic models extracted from modern complex designs result in a large number of passive elements that introduce…

Numerical Analysis · Mathematics 2023-11-16 Christos Giamouzis , Dimitrios Garyfallou , Anastasis Vagenas , Nestor Evmorfopoulos

Turbulent flow control has numerous applications and building reduced-order models (ROMs) of the flow and the associated feedback control laws is extremely challenging. Despite the complexity of building data-driven ROMs for turbulence, the…

Fluid Dynamics · Physics 2021-07-19 Arvind T. Mohan , Kaushik Nagarajan , Daniel Livescu

A linear non-modal mechanism for transient amplification of perturbation energy is known to trigger sub-critical transition to turbulence in many shear flows. Feedback control strategies for minimizing this transient energy growth can be…

Fluid Dynamics · Physics 2019-07-04 Aniketh Kalur , Maziar S. Hemati

This paper deals with the numerical modeling of flow around and through a porous obstacle by a reduced order model (ROM) obtained by Galerkin projection of the Navier-Stokes equations onto a Proper Orthogonal Decomposition (POD) reduced…

Fluid Dynamics · Physics 2023-07-24 Cyrille Allery , Claudine Beghein , Claire Dubot , Fabien Dubot

A dynamical low-rank approximation is developed for reduced-order modeling (ROM) of the filtered density function (FDF) transport equation, which is utilized for large eddy simulation (LES) of turbulent reacting flows. In this methodology,…

Fluid Dynamics · Physics 2025-03-25 Aidyn Aitzhan , Peyman Givi , Hessam Babaee

A space-time-parameters structure of parametric parabolic PDEs motivates the application of tensor methods to define reduced order models (ROMs). Within a tensor-based ROM framework, the matrix SVD - a traditional dimension reduction…

Numerical Analysis · Mathematics 2024-08-22 Alexander V. Mamonov , Maxim A. Olshanskii

We examine an analytic variational inference scheme for the Gaussian Process State Space Model (GPSSM) - a probabilistic model for system identification and time-series modelling. Our approach performs variational inference over both the…

Machine Learning · Statistics 2018-12-11 Alessandro Davide Ialongo , Mark van der Wilk , Carl Edward Rasmussen

Simulating physical systems governed by Lagrangian dynamics often entails solving partial differential equations (PDEs) over high-resolution spatial domains, leading to significant computational expense. Reduced-order modeling (ROM)…

Machine Learning · Computer Science 2026-03-04 Hrishikesh Viswanath , Yue Chang , Aleksey Panas , Julius Berner , Peter Yichen Chen , Aniket Bera

In this paper, the control problem for underactuated systems in the presence of external disturbances and model uncertainties is considered. An adaptive fuzzy sliding mode controller (AFSMC) is proposed to solve the problem, satisfying the…

Optimization and Control · Mathematics 2017-02-10 Mohammad Mahdi Azimi , Hamid Reza Koofigar , Mehdi Edrisi

This work proposes novel techniques for the efficient numerical simulation of parameterized, unsteady partial differential equations. Projection-based reduced order models (ROMs) such as the reduced basis method employ a (Petrov-)Galerkin…

Numerical Analysis · Mathematics 2023-12-05 Nicholas Mueller , Santiago Badia

This paper develops a direct data-driven framework for constructing reduced-order models (ROMs) of discrete-time linear dynamical systems with unknown dynamics and process disturbances. The proposed scheme enables controller synthesis on…

Systems and Control · Electrical Eng. & Systems 2026-03-27 Behrad Samari , Henrik Sandberg , Karl H. Johansson , Abolfazl Lavaei

In this work, we develop reduced order models (ROMs) to predict solutions to a multiscale kinetic transport equation with a diffusion limit under the parametric setting. When the underlying scattering effect is not sufficiently strong, the…

Numerical Analysis · Mathematics 2025-05-14 Tianyu Jin , Zhichao Peng , Yang Xiang

We present a comparative computational study of two stabilized Reduced Order Models (ROMs) for the simulation of convection-dominated incompressible flow (Reynolds number of the order of a few thousands). Representative solutions in the…

Fluid Dynamics · Physics 2024-05-01 Pierfrancesco Siena , Michele Girfoglio , Annalisa Quaini , Gianluigi Rozza

In this paper, we propose an equation-based parametric Reduced Order Model (ROM), whose accuracy is improved with data-driven terms added into the reduced equations. These additions have the aim of reintroducing contributions that in…

Numerical Analysis · Mathematics 2024-06-07 Anna Ivagnes , Giovanni Stabile , Gianluigi Rozza

Low-order frequency response models for power systems have a decades-long history in optimization and control problems such as unit commitment, economic dispatch, and wide-area control. With a few exceptions, these models are built upon the…

Systems and Control · Electrical Eng. & Systems 2025-11-10 Marena Trujillo , Amir Sajadi , Bri-Mathias Hodge