Concept

Parametric model

Publications associées (127)

Data-driven LPV Disturbance Rejection Control with IQC-based Stability Guarantees for Rate-bounded Scheduling Parameter Variations

In this paper, the challenge of asymptotically rejecting sinusoidal disturbances with unknown time-varying frequency and bounded rate is explored. A novel data-driven approach for designing linear parameter-varying (LPV) con- troller is introduced, leverag ...

2024

Higher Order Asymptotics: Applications to Satellite Conjunction and Boundary Problems

Soumaya Elkantassi

Higher-order asymptotics provide accurate approximations for use in parametric statistical modelling. In this thesis, we investigate using higher-order approximations in two-specific settings, with a particular emphasis on the tangent exponential model. Th ...

EPFL2023

Climate risk and vulnerability assessment tool

Changing climatic conditions and increase of extreme events induced by climate change have impacts on non- adapted infrastructures, leading to destruction, damage costs and indirect impacts. To adapt infrastructures to those new conditions, there is a need ...

2023

Data-driven fixed-structure frequency-based H2 and H∞ controller design

Alireza Karimi, Vaibhav Gupta, Philippe Louis Schuchert

The frequency response data of a generalized system is used to design fixed-structure controllers for the H2 and H∞ synthesis problem. The minimization of the two and infinity norm of the transfer function between the exogenous inputs and performance outpu ...

2023

Experimental data-driven model predictive control of a hospital HVAC system during regular use

Colin Neil Jones, Christophe Salzmann, Emilio Maddalena

Herein we report a multi-zone, heating, ventilation and air-conditioning (HVAC) control case study of an industrial plant responsible for cooling a hospital surgery center. The adopted approach to guaranteeing thermal comfort and reducing electrical energy ...

ELSEVIER SCIENCE SA2022

Alpha-NML Universal Predictors

Michael Christoph Gastpar, Marco Bondaschi

Inspired by Sibson’s alpha-mutual information, we introduce a new parametric class of universal predictors. This class interpolates two well-known predictors, the mixture estimator, that includes the Laplace and the Krichevsky-Trofimov predictors, and the ...

2022

Design and evaluation of digital tools to expand experience in vocational education

Kevin Gonyop Kim

Vocational education and training (VET) is the most popular form of upper-secondary education in Switzerland, with more than two-thirds of the teenagers enrolling in a VET program after finishing their compulsory education. The vast majority of the Swiss V ...

EPFL2022

Learning new physics from an imperfect machine

Raffaele Tito D'Agnolo, Andrea Wulzer

We show how to deal with uncertainties on the Standard Model predictions in an agnostic new physics search strategy that exploits artificial neural networks. Our approach builds directly on the specific Maximum Likelihood ratio treatment of uncertainties a ...

SPRINGER2022

Random conical tilt reconstruction without particle picking in cryo-electron microscopy

Nicolas Boumal

A method is proposed to reconstruct the 3D molecular structure from micrographs collected at just one sample tilt angle in the random conical tilt scheme in cryo-electron microscopy. The method uses autocorrelation analysis on the micrographs to estimate f ...

INT UNION CRYSTALLOGRAPHY2022

Improving parametric mass modelling of lensing clusters through a perturbative approach

Jean-Paul Richard Kneib, Benjamin Yvan Alexandre Clement, Benjamin Emmanuel Nicolas Beauchesne, Johan Richard

We present a new method to model the mass distribution of galaxy clusters that combines a parametric and a free-form approach to reconstruct cluster cores with strong lensing constraints. It aims at combining the advantages of both approaches, by keeping t ...

OXFORD UNIV PRESS2021

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