Data-Driven Unknown-Input Observers and State Estimation

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This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...

A key challenge across many disciplines is to extract meaningful information from data which is often obscured by noise. These datasets are typically represented as large matrices. Given the current trend of ever-increasing data volumes, with datasets grow ...

The p-Laplacian problem -del & sdot; ((mu + |del u|(p-2))del u) = f is considered, where mu is a given positive number. An anisotropic a posteriori residual-based error estimator is presented. The error estimator is shown to be equivalent, up to higher ord ...

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

Context. Gaia DR3 has offered the scientific community a remarkable dataset of approximately one million spectra acquired with the radial velocity spectrometer (RVS) in the calcium II triplet region, which is well suited to identify very metal-poor (VMP) s ...

This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the recent publication entitled “3D printing of customizable transient bioelectronics and sensors”. This work aims to study and demonstrate ...

Dataset corresponding to the following manuscript: Slagter, A., Setyadji, J.A., Vogt, E.L. et al. Nanoindentation Hardness and Modulus of Al2O3–SiO2–CaO and MnO–SiO2–FeO Inclusions in Iron. Metall Mater Trans A (2024). https://doi.org/10.1007/s11661-024-0 ...

This document contains all the data and the details of the analysis used in the manuscript titled " Control of Ge island coalescence for the formation of nanowires on silicon." https://doi.org/10.1039/D3NH00573A ...

This paper presents the experimental validation of a linear recursive state estimation (SE) process for hybrid AC/DC microgrids proposed in the authors' previous work. The SE uses a unified and linear measurement model that relies on the use of synchronize ...

The increasing availability of sensing techniques provides a great opportunity for engineers to design state estimation methods, which are optimal for the system under observation and the observed noise patterns. However, these patterns often do not fulfil ...

This dataset contains aerosol optical absorption coefficients at seven different wavelengths (babs(λ)), averaged to 10 min time resolution, measured during the year-long MOSAiC expedition from October 2019 to September 2020. The measurements were performed ...

Selection bias may arise when data have been chosen in a way that subsequent analysis does not account for. Such bias can arise in climate event attribution studies that are performed rapidly after a devastating "trigger event'', whose occurrence correspon ...

An a posteriori error estimator based on an equilibrated flux reconstruction is proposed for defeaturing problems in the context of finite element discretizations. Defeaturing consists in the simplification of a geometry by removing features that are consi ...

Simulation script for the paper "Regularization for distributionally robust state estimation and prediction". Run tests/test_cdc.py to reproduce results. Extended versions can be found at https://github.com/DecodEPFL/. ...

This dataset contains the bulk size-resolved chemical composition and mass concentration of non-refractory submicron aerosols (NR-PM1) measured during the MOSAiC expedition from October 2019 to July 2020. These include the mass concentrations of sulfate (S ...

Is it possible to detect if the sample paths of a stochastic process almost surely admit a finite expansion with respect to some/any basis? The determination is to be made on the basis of a finite collection of discretely/noisily observed sample paths. We ...

Self-exciting point processes, widely used to model arrival phenomena in nature and society, are often difficult to identify. The estimation becomes even more challenging when arrivals are recorded only as bin counts on a finite partition of the observatio ...

A novel approach for robust controller synthesis, which models uncertainty as an elliptical set, is proposed in the paper. Given a set of frequency response functions of linear time-invariant (LTI) multiple-input multiple-output (MIMO) systems, the approac ...

In the Large Hadron Collider, the beam losses are continuously measured for machine protection. By design, most of the particle losses occur in the collimation system, where the particles with high oscilla-tion amplitudes or large momentum error are scrape ...

This paper proposes a novel method to improve georeferencing of airborne laser scanning by improved trajectory estimation using Vehicle Dynamic Model. In Vehicle Dynamic Model (VDM), the relationship between the dynamics of the platform and control inputs ...

Data-Driven Unknown-Input Observers and State Estimation

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Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Spectral Estimators for High-Dimensional Matrix Inference

Anisotropic Adaptive Finite Elements for a p-Laplacian Problem

Robust machine learning for neuroscientific inference

Gaia's brightest very metal-poor (VMP) stars Metallicity catalogue of a thousand VMP stars from Gaia's radial velocity spectrometer spectra

Dataset for '3D printing of customizable transient bioelectronics and sensors'

Nanoindentation hardness and modulus of Al2O3-SiO2-CaO and MnO-SiO2-FeO inclusions in iron

Data set for control of Ge island coalescence for the formation of nanowires on silicon

Experimental Validation of a Unified and Linear State Estimation Method for Hybrid AC/DC Microgrids

Regularization for distributionally robust state estimation and prediction

Aerosol optical absorption coefficients at seven wavelengths in 10 min resolution measured in the Swiss container during MOSAiC 2019/2020

Timing and spatial selection bias in rapid extreme event attribution

An equilibrated flux a posteriori error estimator for defeaturing problems

Regularization for distributionally robust state estimation and prediction

Bulk size-resolved chemical composition and mass concentration of non-refractory submicron aerosols measured in the Swiss container during MOSAiC 2019/2020

Detecting whether a stochastic process is finitely expressed in a basis

Estimation of Self-Exciting Point Processes from Time-Censored Data

Data-driven IQC-Based Robust Control Design for Hybrid Micro-disturbance Isolation Platform

Data-driven modeling of beam loss in the LHC

Model-based constraints for trajectory determination of quad-copters: Design, calibration & merits for direct orientation