On identification methods for direct data-driven controller tuning

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The automatic design of well-performing robotic controllers is still an unsolved problem due to the inherently large parameter space and noisy, often hard-to-define performance metrics, especially when sequential tasks need to be accomplished. Distal contr ...

Environmental noise, mostly related to human activities, has an immense impact on public health. The development of noise reduction technologies is paramount in addressing this problem. Because of practical and economic reasons, a compact, broadband, light ...

In wearable-based human activity recognition (HAR) research, one of the major challenges is the large intra-class variability problem. The collected activity signal is often, if not always, coupled with noises or bias caused by personal, environmental, or ...

We experimentally demonstrate the advantages of gamma detection for noise measurements to deter-mine the prompt neutron decay constant a of a nuclear reactor using the power spectral density (PSD) method, coupled to a new uncertainty estimation scheme base ...

Eccentricity has emerged as a potentially useful tool for helping to identify the origin of black hole mergers. However, eccentric templates can be computationally very expensive owing to the large number of harmonics, making statistical analyses to distin ...

In digital imaging, especially in the process of data acquisition and transmission, images are often affected by impulsive noise. Therefore, it is essential to remove impulsive noise from images before any further processing. Due to the remarkable performa ...

A Mach-Zehnder Interferometer (MZI) based optical fibre sensing technique, developed and patented by EPFL, is an efficient and economical way to detect hotspots in High Temperature Superconductor (HTS) applications. Due to the MZI sensitivity being a compo ...

Purpose: We have introduced an artificial intelligence framework, 31P-SPAWNN, in order to fully analyze phosphorus-31 (P-31) magnetic resonance spectra. The flexibility and speed of the technique rival traditional least-square fitting methods, with the per ...

This article addresses the problem of simultaneous distributed state estimation, and control of linear systems with linear state feedback, subjected to process, and measurement noise, under the constraints of quantized, and rate-limited network data transm ...

The paper considers the problem of estimating the parameters of the compound admittance matrix of three-phase untransposed low-and medium-voltage electrical distribution networks using synchrophasor measurements from phasor measurement units (PMUs). The wo ...

This database is meant to evaluate the performance of denoising and delineation algorithms for PPG signals affected by noise. The noise generator allows applying the algorithms under test to an artificially corrupted reference PPG signal and comparing its ...

Image classification has significantly improved using deep learning. This is mainly due to convolutional neural networks (CNNs) that are capable of learning rich feature extractors from large datasets. However, most deep learning classification methods are ...

On identification methods for direct data-driven controller tuning

Chattez avec Graph Search

A Noise-Resistant Mixed-Discrete Particle Swarm Optimization Algorithm for the Automatic Design of Robotic Controllers

Plasma-based Electroacoustic Actuator for Broadband Sound Absorption

Learning Disentangled Behaviour Patterns for Wearable-based Human Activity Recognition

High accuracy measurement of the prompt neutron decay constant in CROCUS using Gamma Noise and bootstrapped uncertainties

An Efficient Signal-to-noise Approximation for Eccentric Inspiraling Binaries

Impulsive noise removal via a blind CNN enhanced by an iterative post-processing

Optical fibre based quench detection in HTS applications using machine learning classifiers

In vivo magnetic resonance P-31-Spectral Analysis With Neural Networks: 31P-SPAWNN

A Distributed Luenberger Observer for Linear State Feedback Systems With Quantized and Rate-Limited Communications

Compound Admittance Matrix Estimation of Three-phase Untransposed Power Distribution Grids using Synchrophasor Measurements

Synthetic realistic noise-corrupted PPG database and noise generator for the evaluation of PPG denoising and delineation algorithms

Fidelity Estimation Improves Noisy-Image Classification with Pretrained Networks