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A structure preserving proper orthogonal decomposition reduce-order modeling approach has been developed in [Gong et al. 2017] for the Hamiltonian system, which uses the traditional framework of Galerkin projection-based model reduction but…

Numerical Analysis · Mathematics 2021-03-03 Zhu Wang

This paper proposes a new methodology in linear time-periodic (LTP) system identification. In contrast to previous methods that totally separate dynamics at different tag times for identification, the method focuses on imposing appropriate…

Systems and Control · Electrical Eng. & Systems 2021-11-10 Mingzhou Yin , Andrea Iannelli , Mohammad Khosravi , Anilkumar Parsi , Roy S. Smith

In this paper, existence conditions and a design procedure of reduced-order switched positive observers for continuous- and discrete-time switched positive linear systems with uncertainty are established. In the analyzed class, arbitrary…

Systems and Control · Electrical Eng. & Systems 2025-05-15 Naohisa Otsuka , Daiki Kakehi , Przemysław Ignaciuk

We derive a posteriori error estimators for an optimal control problem governed by a convection-reaction-diffusion equation; control constraints are also considered. We consider a family of low-order stabilized finite element methods to…

Numerical Analysis · Mathematics 2017-04-24 Alejandro Allendes , Enrique Otarola , Richard Rankin

Orthogonal projection-based reduced order models (PROM) are the output of widely-used model reduction methods. In this work, a novel product form is derived for the reduction error system of these reduced models, and it is shown that any…

Systems and Control · Electrical Eng. & Systems 2022-01-03 Noam Leiter , Daniel Zelazo

An adaptive scheme to generate reduced-order models for parametric nonlinear dynamical systems is proposed. It aims to automatize the POD-Greedy algorithm combined with empirical interpolation. At each iteration, it is able to adaptively…

Numerical Analysis · Mathematics 2021-10-13 Sridhar Chellappa , Lihong Feng , Peter Benner

It is well known that Lawson methods suffer from a severe order reduction when integrating initial boundary value problems where the solutions are not periodic in space or do not satisfy enough conditions of annihilation on the boundary.…

Numerical Analysis · Mathematics 2019-09-30 Begoña Cano , Nuria Reguera

This paper directly builds upon previous work where we introduced new reduced basis a posteriori error bounds for parametrized saddle point problems based on Brezzi's theory. We here sharpen these estimates for the special case of a…

Numerical Analysis · Mathematics 2012-11-06 Anna-Lena Gerner , Karen Veroy

This work proposes a structure-preserving model reduction method for marginally stable linear time-invariant (LTI) systems. In contrast to Lyapunov-stability-based approaches---which ensure the poles of the reduced system remain in the open…

Dynamical Systems · Mathematics 2017-04-24 Liqian Peng , Kevin Carlberg

This paper presents a partial state-feedback reduced-order switching predictive model designed to support the next-generation lithography roadmap. The proposed approach addresses the trade-off between increasing the number of measurements…

Optimization and Control · Mathematics 2025-10-16 Raaja Ganapathy Subramanian , Barry Moest , Bart Paarhuis

In this work we propose tailored model order reduction for varying boundary optimal control problems governed by parametric partial differential equations. With varying boundary control, we mean that a specific parameter changes where the…

Numerical Analysis · Mathematics 2024-01-22 Maria Strazzullo , Fabio Vicini

This paper introduces a quadrature-free, non-intrusive approach to balanced truncation for both continuous-time and discrete-time systems. The method non-intrusively constructs reduced-order models using available transfer function samples…

Systems and Control · Electrical Eng. & Systems 2026-02-20 Umair Zulfiqar

Bounded-input bounded-output stability condition of linear time invariant (LTI) distributed-order system over integral interval $(0,1)$ has been established for the first time. Two cases about weighting function of the distributed order are…

Systems and Control · Computer Science 2012-12-18 Zhuang Jiao , YangQuan Chen , Yi-Sheng Zhong

Boosting techniques and neural networks are particularly effective machine learning methods for insurance pricing. Often in practice, there are nevertheless endless debates about the choice of the right loss function to be used to train the…

Machine Learning · Statistics 2021-07-12 Michel Denuit , Arthur Charpentier , Julien Trufin

For some typical and widely used non-convex half-quadratic regularization models and the Ambrosio-Tortorelli approximate Mumford-Shah model, based on the Kurdyka-\L ojasiewicz analysis and the recent nonconvex proximal algorithms, we…

Optimization and Control · Mathematics 2021-07-30 Shengxiang Deng , Ismail Ben Ayed , Hongpeng Sun

A highly anticipated use of quantum computers is the simulation of complex quantum systems including molecules and other many-body systems. One promising method involves directly applying a linear combination of unitaries (LCU) to…

Quantum Physics · Physics 2022-02-02 Richard Meister , Simon C. Benjamin , Earl T. Campbell

Reduced Order Models (ROMs) form essential tools across engineering domains by virtue of their function as surrogates for computationally intensive digital twinning simulators. Although purely data-driven methods are available for ROM…

Computational Engineering, Finance, and Science · Computer Science 2025-04-14 Konstantinos Vlachas , Thomas Simpson , Anthony Garland , D. Dane Quinn , Charbel Farhat , Eleni Chatzi

This paper examines the construction of rth-order truncated balanced realizations via tangential interpolation at r specified interpolation points. It is demonstrated that when the truncated Hankel singular values are negligible-that is,…

Systems and Control · Electrical Eng. & Systems 2025-04-11 Umair Zulfiqar , Zhi-Hua Xiao , Qiu-yan Song , Victor Sreeram

A multi-fidelity framework is established and demonstrated for prediction of combustion instabilities in rocket engines. The major idea is to adapt appropriate fidelity modeling approaches for different components in a rocket engine to…

Fluid Dynamics · Physics 2019-05-31 Jiayang Xu , Cheng Huang , Karthik Duraisamy

Trotterization is one of the central approaches for simulating quantum many-body dynamics on quantum computers or tensor networks. In addition to its simple implementation, recent studies have revealed that its error and cost can be reduced…

Quantum Physics · Physics 2025-10-17 Kaoru Mizuta , Tomotaka Kuwahara