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Receding horizon optimal control problems compute the solution at each time step to operate the system on a near-optimal path. However, in many practical cases, the boundary conditions, such as external inputs, constraint equations, or the…

Optimization and Control · Mathematics 2021-02-02 Abhishek Gupta , Shreshta Rajakumar Deshpande , Marcello Canova

We describe in detail how to eliminate nonphysical degrees of freedom in the Lagrangian and Hamiltonian formulations of a constrained system. Two important and distinct steps in our method are the fixing of ambiguities in the dynamics and…

General Relativity and Quantum Cosmology · Physics 2010-04-06 J M Pons , L C Shepley

We present a multi-scale modeling and simulation framework for low-Reynolds number hydrodynamics of shape-changing immersed objects, e.g., biological microswimmers and active surfaces. The key idea is to consider principal shape changes as…

Soft Condensed Matter · Physics 2020-12-18 Anton Solovev , Benjamin M. Friedrich

This study introduces a novel approach for deriving the governing equations of the musculoskeletal system in the human body. The proposed formalism offers a framework to effectively incorporate the kinematic characteristics of biological…

Applied Physics · Physics 2023-07-26 Hossein Ehsani

This paper presents tractable reformulations of topology optimization problems of structures subject to frictionless unilateral contact conditions. Specifically, we consider stiffness maximization problems of trusses and continua. Based on…

Optimization and Control · Mathematics 2020-11-17 Yoshihiro Kanno

In this paper, considering a braided continuum soft-robot, whose radial deformation is constrained but elongation is assumed, a quasi-Lagrangian model is proposed that meets the Lagrangian models properties, including a well-posed input…

Deep learning models are able to approximate one specific dynamical system but struggle at learning generalisable dynamics, where dynamical systems obey the same laws of physics but contain different numbers of elements (e.g., double- and…

Machine Learning · Computer Science 2022-07-05 Yupu Lu , Shijie Lin , Guanqi Chen , Jia Pan

We consider tracking control for multibody systems which are modelled using holonomic and nonholonomic constraints. Furthermore, the systems may be underactuated and contain kinematic loops and are thus described by a set of…

Optimization and Control · Mathematics 2021-02-11 Thomas Berger , Svenja Drücker , Lukas Lanza , Timo Reis , Robert Seifried

We propose a parameter optimization method for achieving static equilibrium of discrete elastic rods. Our method simultaneously optimizes material stiffness and rest shape parameters under box constraints to exactly enforce zero net force…

Graphics · Computer Science 2025-10-16 Tetsuya Takahashi , Christopher Batty

In this paper, we construct and analyze a multiscale (finite element) method for parabolic problems with heterogeneous dynamic boundary conditions. As origin, we consider a reformulation of the system in order to decouple the discretization…

Numerical Analysis · Mathematics 2020-09-16 Robert Altmann , Barbara Verfürth

Building towards a more covariant approach to canonical classical and quantum gravity we outline an approach to constrained dynamics that de-emphasizes the role of the Hamiltonian phase space and highlights the role of the Lagrangian phase…

General Relativity and Quantum Cosmology · Physics 2008-11-26 Andrew Randono

Energetic particle effects in magnetic confinement fusion devices are commonly studied by hybrid kinetic-fluid simulation codes whose underlying continuum evolution equations often lack the correct energy balance. While two different…

Plasma Physics · Physics 2019-01-23 Alexander R. D. Close , Joshua W. Burby , Cesare Tronci

Trajectory optimization is an efficient approach for solving optimal control problems for complex robotic systems. It relies on two key components: first the transcription into a sparse nonlinear program, and second the corresponding solver…

Robotics · Computer Science 2022-10-31 Wilson Jallet , Antoine Bambade , Nicolas Mansard , Justin Carpentier

This paper develops a robust fixed time optimization framework for constrained problems that guarantees exact constraint satisfaction and convergence to KKT points within fixed time , independent of initial conditions. The approach treats…

Optimization and Control · Mathematics 2026-05-27 Baby Diana , Priyanka Singh , Shyam Kamal , Sandip Ghosh , Bijnan Bandyopadhyay

In this paper, we present a novel general framework grounded in the factor graph theory to solve kinematic and dynamic problems for multi-body systems. Although the motion of multi-body systems is considered to be a well-studied problem and…

Robotics · Computer Science 2021-07-27 José-Luis Blanco-Claraco , Antonio Leanza , Giulio Reina

This paper is concerned with the application of the theory of quasivelocities for optimal control for underactuated mechanical systems. Using this theory, we convert the original problem in a variational second-order lagrangian system…

Mathematical Physics · Physics 2015-05-18 L. Colombo , D. Martin de Diego

This paper introduces a sharp-interface approach to simulating fluid-structure interaction involving flexible bodies described by general nonlinear material models and across a broad range of mass density ratios. This new flexible-body…

Constrained mechanical multibody systems arise in many important applications like robotics, vehicle and machinery dynamics and biomechanics of locomotion of humans. These systems are described by the Euler-Lagrange equations which are…

Numerical Analysis · Mathematics 2016-05-31 Brahim Benhammouda

We propose a new approach in Lagrangian formalism for studying the fluid dynamics on noncommutative space. Starting with the Poisson bracket for single particle, a map from canonical Lagrangian variables to Eulerian variables is constructed…

High Energy Physics - Theory · Physics 2018-02-20 Kai Ma

In this paper, we propose a novel conservative formulation for solving kinetic equations via neural networks. More precisely, we formulate the learning problem as a constrained optimization problem with constraints that represent the…

Numerical Analysis · Mathematics 2021-06-24 Hyung Ju Hwang , Hwijae Son
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