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Publications associées (202)

Moving Horizon Estimation for Model Predictive Perimeter Control of Multi-region MFD Networks

Nikolaos Geroliminis, Isik Ilber Sirmatel

Management of road traffic in urban settings remains a challenging problem. Perimeter control schemes proposed to alleviate congestion in large-scale urban networks usually assume noise-free measurements of the traffic state, which is problematic since mea ...

2019

Moving Horizon Demand and State Estimation for Model Predictive Perimeter Control of Large-scale Urban Networks

Nikolaos Geroliminis, Isik Ilber Sirmatel

Perimeter control schemes proposed to alleviate congestion in large-scale urban networks usually assume perfect knowledge of the accumulation state and inflow demands, both requiring information about the origins and destinations of drivers. Such assumptio ...

IEEE2019

Concept of Variants and Invariants for Reaction Systems, with Application to Estimation, Control and Optimization

Diogo Filipe Mateus Rodrigues

The concept of reaction variants and invariants for lumped reaction systems has been known for several decades. Its applications encompass model identification, data reconciliation, state estimation and control using kinetic models. In this thesis, the con ...

EPFL2018

Orientation-Dispersed Apparent Axon Diameter via Multi-Stage Spherical Mean Optimization

Jean-Philippe Thiran, Marco Pizzolato

The estimation of the apparent axon diameter (AAD) via diffusion MRI is affected by the incoherent alignment of single axons around its axon bundle direction, also known as orientational dispersion. The simultaneous estimation of AAD and dispersion is chal ...

SPRINGER-VERLAG BERLIN2018

Robust model updating methodology for estimating worst-case load capacity of existing bridges

Ian Smith, Didier Vernay, François-Xavier Favre

High-value infrastructure elements, such as bridges, are typically over-designed. Model-updating techniques are useful for estimating the reserve load capacity (beyond safety factors) of bridges and this improves sustainability through good asset-managemen ...

2018

Perception-aware Receding Horizon Navigation for MAVs

Davide Scaramuzza

To reach a given destination safely and accurately, a micro aerial vehicle needs to be able to avoid obstacles and minimize its state estimation uncertainty at the same time. To achieve this goal, we propose a perception-aware receding horizon approach. In ...

2018

Deep convolutional neural networks for estimating porous material parameters with ultrasound tomography

Jan Sickmann Hesthaven

We study the feasibility of data based machine learning applied to ultrasound tomography to estimate water-saturated porous material parameters. In this work, the data to train the neural networks is simulated by solving wave propagation in coupled porovis ...

2018

Wasserstein Distributionally Robust Kalman Filtering

Daniel Kuhn, Viet Anh Nguyen, Soroosh Shafieezadeh Abadeh, Peyman Mohajerin Esfahani

We study a distributionally robust mean square error estimation problem over a nonconvex Wasserstein ambiguity set containing only normal distributions. We show that the optimal estimator and the least favorable distribution form a Nash equilibrium. Despit ...

2018

The Mutual Information in Random Linear Estimation Beyond i.i.d. Matrices

Nicolas Macris, Florent Gérard Krzakala, Jean François Emmanuel Barbier

There has been definite progress recently in proving the variational single-letter formula given by the heuristic replica method for various estimation problems. In particular, the replica formula for the mutual information in the case of noisy linear esti ...

IEEE2018

Constrained multi-rate state estimator incorporating delayed measurements

Dominique Bonvin, Michael Amrhein, Sriniketh Srinivasan

Frequent and accurate concentration estimates are important for the on-line control and optimization of chemical reaction systems. Such estimates can be obtained using state estimation methods that fuse frequent (fast) delay-free on-line measurements with ...

IEEE2017

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