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Mechanical systems are often characterized only by their response to certain loads known from experiments or simulations. The obtained data can be used for various purposes: system analysis, design of mathematical models, or construction of…

Dynamical Systems · Mathematics 2026-01-05 Yevgeniya Filanova , Igor Pontes Duff , Pawan Goyal , Peter Benner

This paper presents a port-Hamiltonian formulation of vehicle-manipulator systems (VMS), a broad class of robotic systems including aerial manipulators, underwater manipulators, space robots, and omnidirectional mobile manipulators. Unlike…

Systems and Control · Electrical Eng. & Systems 2026-03-19 Ramy Rashad

A method for the nonintrusive and structure-preserving model reduction of canonical and noncanonical Hamiltonian systems is presented. Based on the idea of operator inference, this technique is provably convergent and reduces to a…

Machine Learning · Computer Science 2023-06-27 Anthony Gruber , Irina Tezaur

In this work we make use of Livens principle (sometimes also referred to as Hamilton-Pontryagin principle) in order to obtain a novel structure-preserving integrator for mechanical systems. In contrast to the canonical Hamiltonian equations…

Computational Engineering, Finance, and Science · Computer Science 2025-06-24 Philipp L. Kinon , Peter Betsch

In this work, we investigate a model order reduction scheme for high-fidelity nonlinear structured parametric dynamical systems. More specifically, we consider a class of nonlinear dynamical systems whose nonlinear terms are polynomial…

Dynamical Systems · Mathematics 2023-01-24 Pawan Goyal , Igor Pontes Duff , Peter Benner

An equation is obtained to find the Lagrangian for a one-dimensional autonomous system. The continuity of the first derivative of its constant of motion is assumed. This equation is solved for a generic nonconservative autonomous system…

Mathematical Physics · Physics 2009-11-10 G. Gonzalez

The study of mechanical systems on Lie algebroids permits an understanding of the dynamics described by a Lagrangian or Hamiltonian function for a wide range of mechanical systems in a unified framework. Systems defined in tangent bundles,…

Mathematical Physics · Physics 2018-03-02 Ligia Abrunheiro , Leonardo Colombo

Optimization problems with convex quadratic cost and polyhedral constraints are ubiquitous in signal processing, automatic control and decision-making. We consider here an enlarged problem class that allows to encode logical conditions and…

Optimization and Control · Mathematics 2026-04-09 Alberto De Marchi

In this work we demonstrate that SVD-based model reduction techniques known for ordinary differential equations, such as the proper orthogonal decomposition, can be extended to stochastic differential equations in order to reduce the…

Numerical Analysis · Mathematics 2024-02-01 Tomasz M. Tyranowski

A simple general theorem is used as a tool that generates nonlocal constants of motion for Lagrangian systems. We review some cases where the constants that we find are useful in the study of the systems: the homogeneous potentials of…

Dynamical Systems · Mathematics 2020-09-28 Gianluca Gorni , Gaetano Zampieri

In this work we consider (hierarchical, Lagrange) reduced basis approximation and a posteriori error estimation for elasticity problems in affinley parametrized geometries. The essential ingredients of the methodology are: a Galerkin…

Numerical Analysis · Mathematics 2018-01-23 Dinh Bao Phuong Huynh , Federico Pichi , Gianluigi Rozza

The paper proposes an approach for the efficient model order reduction of dynamic contact problems in linear elasticity. Instead of the augmented Lagrangian method that is widely used for mechanical contact problems, we prefer here the…

Numerical Analysis · Mathematics 2021-07-27 Diana Manvelyan , Bernd Simeon , Utz Wever

In this paper we show that a variational reduction procedure can be defined for Lagrangian systems subject to scaling symmetries (i.e. Lagrangian systems defined by a homogenous Lagrangian function), in such a way that the trajectories of…

Differential Geometry · Mathematics 2026-05-08 Javier Fernández , Sergio Grillo , Juan Carlos Marrero , Edith Padrón

Hamiltonian operator inference has been developed in [Sharma, H., Wang, Z., Kramer, B., Physica D: Nonlinear Phenomena, 431, p.133122, 2022] to learn structure-preserving reduced-order models (ROMs) for Hamiltonian systems. The method…

Numerical Analysis · Mathematics 2025-07-21 Yuwei Geng , Lili Ju , Boris Kramer , Zhu Wang

The energy shaping method, Controlled Lagrangian, is a well-known approach to stabilize the under-actuated Euler Lagrange (EL) systems. In this approach, to construct a control rule, some nonlinear, nonhomogeneous partial differential…

Systems and Control · Electrical Eng. & Systems 2020-07-06 Huseyin Alpaslan Yildiz , Leyla Goren-Sumer

A second order accurate numerical scheme is proposed and implemented for the Landau-Lifshitz-Gilbert equation, which models magnetization dynamics in ferromagnetic materials, with large damping parameters. The main advantages of this method…

Computational Physics · Physics 2022-01-26 Yongyong Cai , Jingrun Chen , Cheng Wang , Changjian Xie

A detailed program is proposed in the Lagrangian formalism to investigate the dynamical behavior of a theory with singular Lagrangian. This program goes on, at different levels, parallel to the Hamiltonian analysis. In particular, we…

Classical Physics · Physics 2020-03-31 Mohammad Javad Heidari , Ahmad Shirzad

Previous work in the literature has studied the Hamiltonian structure of an R-squared model of gravity with torsion in a closed Friedmann-Robertson-Walker universe. Within the framework of Dirac's theory, torsion is found to lead to a…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Giampiero Esposito , Gabriele Gionti , Giuseppe Marmo , Cosimo Stornaiolo

A structure-preserving kernel ridge regression method is presented that allows the recovery of nonlinear Hamiltonian functions out of datasets made of noisy observations of Hamiltonian vector fields. The method proposes a closed-form…

Machine Learning · Statistics 2025-04-07 Jianyu Hu , Juan-Pablo Ortega , Daiying Yin

This work addresses the imposition of outflow boundary conditions for one-dimensional conservation laws. While a highly accurate numerical solution can be obtained in the interior of the domain, boundary discretization can lead to…

Numerical Analysis · Mathematics 2025-12-09 Carlos Muñoz-Moncayo