Publications associées à An optimal control strategy to design passive thermal cloaks of arbitrary shape

Publications associées (12)

Surface Integral Equations in Computational Electromagnetics: A Comprehensive Overview of Theory, Formulations, Discretization Schemes and Implementations

Computational electromagnetics based on surface integral equations provides accurate and efficient solutions for three-dimensional electromagnetic scattering problems in the frequency domain. In this review paper, we first introduce a complete and detailed ...

2025

Supershear Crack Propagation in Snow Slab Avalanche Release: New Insights From Numerical Simulations and Field Measurements

Bertil Trottet

The release process of dry-snow slab avalanches begins with a localized failure within a porous, weak snow layer beneath a cohesive slab. Subsequently, rapid crack propagation may occur within the weak layer, eventually leading to a tensile fracture across ...

COPERNICUS GESELLSCHAFT MBH2025

Adaptive Interface-Pinns (Adai-Pinns) for Transient Diffusion: Applications to Forward and Inverse Problems in Heterogeneous Media

Brice Tanguy Alphonse Lecampion

We model transient diffusion in heterogeneous materials using a novel physics-informed neural networks framework (PINNs) termed Adaptive interface physics-informed neural networks or AdaI-PINNs (Roy et al. arXiv preprint arXiv:2406.04626, 2024). AdaI-PINNs ...

Elsevier BV2025

Brunovsky Riccati Recursion for Linear Model Predictive Control

Colin Neil Jones, Shaohui Yang

In almost all algorithms for Model Predictive Control (MPC), the most time-consuming step is to solve some form of Linear Quadratic (LQ) Optimal Control Problem (OCP) repeatedly. The commonly recognized best option for this is a Riccati recursion based sol ...

IEEE2025

NoiseNCA: Noisy Seed Improves Spatio-Temporal Continuity of Neural Cellular Automata

Sabine Süsstrunk, Ehsan Pajouheshgar, Yitao Xu

Neural Cellular Automata (NCA) is a class of Cellular Automata where the update rule is parameterized by a neural network that can be trained using gradient descent. In this paper, we focus on NCA models used for texture synthesis, where the update rule is ...

MIT Press2024

Near-Optimal Design of Safe Output-Feedback Controllers From Noisy Data

Giancarlo Ferrari Trecate, Luca Furieri, Baiwei Guo, Andrea Martin

As we transition toward the deployment of data-driven controllers for black-box cyberphysical systems, complying with hard safety constraints becomes a primary concern. Two key aspects should be addressed when input-output data are corrupted by noise: how ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Optimum trajectory learning in musculoskeletal systems with model predictive control and deep reinforcement learning

Henry Markram, Marc-Oliver Gewaltig

From the computational point of view, musculoskeletal control is the problem of controlling high degrees of freedom and dynamic multi-body system that is driven by redundant muscle units. A critical challenge in the control perspective of skeletal joints w ...

2022

Stokes, Gibbs, and Volume Computation of Semi-Algebraic Sets

Matteo Raphael Tacchi

We consider the problem of computing the Lebesgue volume of compact basic semi-algebraic sets. In full generality, it can be approximated as closely as desired by a converging hierarchy of upper bounds obtained by applying the Moment-SOS (sums of squares) ...

SPRINGER2022

Distributed model predictive control of buildings and energy hubs

Colin Neil Jones

Model predictive control (MPC) strategies can be applied to the coordination of energy hubs to reduce their energy consumption. Despite the effectiveness of these techniques, their potential for energy savings are potentially underutilized due to the fact ...

ELSEVIER SCIENCE SA2022

A Posteriori Error Estimation for the Stochastic Collocation Finite Element Approximation of the Heat Equation with Random Coefficients

Fabio Nobile, Eva Vidlicková

In this work we present a residual based a posteriori error estimation for a heat equation with a random forcing term and a random diffusion coefficient which is assumed to depend affinely on a finite number of independent random variables. The problem is ...

Springer, Cham.2021

Time-domain room acoustic simulations with extended-reacting porous absorbers using the discontinuous Galerkin method

Jan Sickmann Hesthaven

This paper presents an equivalent fluid model (EFM) formulation in a three-dimensional time-domain discontinuous Galerkin finite element method framework for room acoustic simulations. Using the EFM allows for the modeling of the extended-reaction (ER) beh ...

ACOUSTICAL SOC AMER AMER INST PHYSICS2020

Compressive Sampling Using Annihilating Filter-Based Low-Rank Interpolation

Kyong Hwan Jin

While the recent theory of compressed sensing provides an opportunity to overcome the Nyquist limit in recovering sparse signals, a solution approach usually takes the form of an inverse problem of an unknown signal, which is crucially dependent on specifi ...

IEEE2017