Linéarité

Applied sciences
Information engineering
Automatique
Théorie du contrôle

Publications associées (30)

À propos
Confidentialité
Mentions légales

Graph Chatbot

KPC: Learning-Based Model Predictive Control with Deterministic Guarantees

Colin Neil Jones, Yuning Jiang, Paul Scharnhorst, Emilio Maddalena

We propose Kernel Predictive Control (KPC), a learning-based predictive control strategy that enjoys deterministic guarantees of safety. Noise-corrupted samples of the unknown system dynamics are used to learn several models through the formalism of non-pa ...

2021

Running Speed Estimation Using Shoe-Worn Inertial Sensors: Direct Integration, Linear, and Personalized Model

Kamiar Aminian, Mathieu Pascal Falbriard, Abolfazl Soltani

The overground speed is a key component of running analysis. Today, most speed estimation wearable systems are based on GNSS technology. However, these devices can suffer from sparse communication with the satellites and have a high-power consumption. In t ...

2021

Continuous-Domain Formulation of Inverse Problems for Composite Sparse-Plus-Smooth Signals

Michaël Unser, Shayan Aziznejad, Thomas Jean Debarre

We present a novel framework for the reconstruction of 1D composite signals assumed to be a mixture of two additive components, one sparse and the other smooth, given a finite number of linear measurements. We formulate the reconstruction problem as a cont ...

2021

Optical rotating torque sensor with nano newton-meter resolution based on a hanging torsion wire

Simon Nessim Henein, Etienne Frédéric Gabriel Thalmann, Billy Nussbaumer

This article presents a novel torque measuring setup working in the nano newton-meter range. The central novelty is a long (1 meter range) thin (diameter of a few tens of micrometers) metallic wire used instead of the relatively stiff torsion zone of the s ...

euspen2021

Reversible and Broad-Range Oxygen Sensing Based on Purely Organic Long-Lived Photoemitters

Esther Amstad, René M. Rossi, Efe Armagan

The detection of oxygen (O-2) by optical sensors is of growing importance, for example, in biology, life science, environmental science, and aerodynamics, where the composition of gases is crucial for many applications. Purely organic optical O-2 sensors a ...

2021

Travel Time Prediction for Congested Freeways With a Dynamic Linear Model

Nikolaos Geroliminis, Semin Kwak

Accurate prediction of travel time is an essential feature to support Intelligent Transportation Systems (ITS). The non-linearity of traffic states, however, makes this prediction a challenging task. Here we propose to use dynamic linear models (DLMs) to a ...

IEEE Institute of Electrical and Electronics Engineers2021

Computational Modeling of the Oxygen Evolution Reaction at Semiconductor-Water Interfaces: A Path Towards Breaking Linear Scaling Relationships

Patrick Gono

Photoelectrochemical water splitting is a promising source of clean, renewable fuel in the form of hydrogen. Despite extensive research endeavors, the widespread adoption of this technology is impeded due to suboptimal catalysts for the oxygen evolution re ...

EPFL2020

High-order based revelation of bifurcation of novel Schatz-inspired metamorphic mechanisms using screw theory

Huijuan Feng

The revelation of mechanism bifurcation is essential in the design and analysis of reconfigurable mechanisms. The first- and second-order based methods have successfully revealed the bifurcation of mechanisms. However, they fail in the novel Schatz-inspire ...

PERGAMON-ELSEVIER SCIENCE LTD2020

Discrete Time Analysis of Phase Detector Linear Range Extension in Sub-Sampling PLL

Yusuf Leblebici, Duygu Kostak

The discrete time analysis of the phase detector linear range extension in the first and the second order sub sampling phase-locked loop (SSPLL) is presented. The aim is to understand how much the stability and the pull-in range are affected by the linear ...

IEEE2020

Learning (from) the Electron Density: Transferability, Conformational and Chemical Diversity

Anne-Clémence Corminboeuf, Ksenia Briling, Alberto Fabrizio, Andrea Grisafi

Machine-learning in quantum chemistry is currently booming, with reported applications spanning all molecular properties from simple atomization energies to complex mathematical objects such as the many-body wavefunction. Due to its central role in density ...

2020

Page 3 sur 3

Computational Modeling of the Oxygen Evolution Reaction at Semiconductor-Water Interfaces: A Path Towards Breaking Linear Scaling Relationships

Patrick Gono

EPFL2020