Publications related to Data-driven controller tuning using the correlation approach

Related publications (36)

Lessons Learned Executing the Non-disruptive Compass Scan Method at Jet Towards Error Field Identification Experiments in Iter

In preparation for error field (EF) identification experiments in ITER, a series of experiments have been conducted at JET to test the portability of the non-disruptive compass scan, a method originally designed and tested in DIII-D (Paz-Soldan et al 2022 ...

IOP Publishing Ltd2025

High-precision control of a robotic arm using frequency-based data-driven methods

Alireza Karimi, Philippe Louis Schuchert

Next-generation motion control systems require fast and precise control. However, advanced control strategies often rely on complex and costly system models. Data-driven methods have been proposed to design high-performance controllers without requiring a ...

2025

Design and implementation of a model-based hierarchical architecture for plasma shape control in the TCV tokamak

Olivier Sauter, Stefano Coda, Federico Alberto Alfredo Felici, Antoine Pierre Emmanuel Alexis Merle, Cristian Galperti, Adriano Mele, Alessandro Tenaglia

Plasma shape control is a fundamental tool for effective tokamak operation, allowing improved plasma performance and the pursuit of challenging scientific objectives. In this framework, the Tokamak á Configuration Variable (TCV) of the École Polytechnique ...

IOP Publishing2025

A Closer Look at Benchmarking Self-supervised Pre-training with Image Classification

Fernando Perez Cruz

Self-supervised learning (SSL) is a machine learning approach where the data itself provides supervision, eliminating the need for external labels. The model is forced to learn about the data's inherent structure or context by solving a pretext task. With ...

SPRINGER2025

Probing the latent hierarchical structure of data via diffusion models

Noam Itzhak Levi, Alessandro Favero, Antonio Sclocchi

High-dimensional data must be highly structured to be learnable. Although the compositional and hierarchical nature of data is often put forward to explain learnability, quantitative measurements establishing these properties are scarce. Likewise, accessin ...

2025

Quantitative analysis of the correlation between body posture quality assessment scores and handwriting quality measures

Pierre Dillenbourg, Barbara Bruno, Daniel Carnieto Tozadore, Chenyang Wang

Various technological applications for body posture correction have been proposed in order to improve handwriting or facilitate its learning for children, under the assumption that a better posture promotes better handwriting. However, very little research ...

Springer Science and Business Media LLC2025

How Gradient Descent Balances Features: A Dynamical Analysis For Two-Layer Neural Networks

Volkan Cevher, Fanghui Liu, Zhenyu Zhu

This paper investigates the fundamental regression task of learning k neurons (a.k.a. teachers) from Gaussian input, using two-layer ReLU neural networks with width m (a.k.a. students) and m, k = O(1), trained via gradient descent under proper initializati ...

2025

Foundations of a New Learning Paradigm in AI Grounded in the Principles of Evolutionary Developmental Biology

Zeki Doruk Erden

Contemporary AI faces important limitations that remain unresolved despite significant successes. Chief among these are the inability to acquire new knowledge without destroying old, the incomprehensible and nonengineerable nature of internal representatio ...

EPFL2025

Advanced control strategies to exploit the hydropower potential enhancing ancillary services provision to the power system

Francesco Gerini

The European Union's Green Deal aims for a 55% reduction in greenhouse gas emissions by 2030. To reach this goal, a massive integration of Renewable Energy Sources (RES) into the power grid is necessary. As RES become a large part of the electricity genera ...

EPFL2024

Design Trade-offs of Second Harmonic Minimization in Solid-State Transformers

Amin Darvishzadeh, Drazen Dujic

In two-stage solid-state transformers (SSTs) equipped with LLC DC/DC converters for galvanic isolation, fixed-frequency open-loop operation of LLC stages has been a straightforward and prevailing design choice. Meanwhile, with a closed-loop-operated LLC co ...

Institute of Electrical and Electronics Engineers (IEEE)2025

A phase transition between positional and semantic learning in a solvable model of dot-product attention

Lenka Zdeborová, Florent Gérard Krzakala, Hugo Chao Cui, Freya Behrens

Many empirical studies have provided evidence for the emergence of algorithmic mechanisms (abilities) in the learning of language models, that lead to qualitative improvements in the model capabilities. Yet, a theoretical characterization of how such mecha ...

2025

Frequency domain data-driven robust and optimal control

Philippe Louis Schuchert

The goal of this thesis is to propose pragmatic solutions to real challenges faced in the industry. The scope of this thesis encompasses two subjects: frequency-based structured controller synthesis for linear time-invariant (LTI) systems on one side, and ...

EPFL2024

Radiation Efficiency and Gain Bounds for Microstrip Patch Antennas

Anja Skrivervik

This article presents bounds on radiation efficiency and gain for microstrip patch antennas, demonstrating close alignment with the performance of classic antenna designs. These bounds serve as effective benchmarks for assessing antenna performance and eva ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2025

Stability Analysis of Input-Series/Output-Parallel Solid-State Transformers Equipped with Second-Order Harmonic Active Power Filters

Drazen Dujic, Andrea Cervone, Tianyu Wei

Solid-State Transformers with Input-Series/Output-Parallel configuration offer a convenient solution for AC/DC conversion due to their scalability and modularity. In this configuration, each module experiences a second-order harmonic ripple caused by local ...

2024

On the use of Cramér-Rao Lower Bound for least-variance circuit parameters identification of Li-ion cells

Mario Paolone, Vladimir Sovljanski

Electrochemical Impedance Spectroscopy (EIS) and Equivalent Circuit Models (ECMs) are widely used to characterize the impedance and estimate parameters of electrochemical systems such as batteries. We use a generic ECM with ten parameters grouped to model ...

2024

Accurate and agile flight with winged drones

Valentin Wüest

Drones hold promise to assist in civilian tasks. To realize this application, future drones must operate within large cities, covering large distances while navigating within cluttered urban landscapes. The increased efficiency of winged drones over rotary ...

EPFL2024

The hindbrain and cortico-reticular pathway in adolescent idiopathic scoliosis

Bénédicte Marie Maréchal

AIM: To characterise the corticoreticular pathway (CRP) in a case -control cohort of adolescent idiopathic scoliosis (AIS) patients using high -resolution slice -accelerated readoutsegmented echo -planar diffusion tensor imaging (DTI) to enhance the discri ...

W B Saunders Co Ltd2024

Extensions of Peer Prediction Incentive Mechanisms

Adam Julian Richardson

As large, data-driven artificial intelligence models become ubiquitous, guaranteeing high data quality is imperative for constructing models. Crowdsourcing, community sensing, and data filtering have long been the standard approaches to guaranteeing or imp ...

EPFL2024

Strategy to systematically design and deploy the ITER plasma control system: A system engineering and model-based design approach

Richard Pitts, Federico Alberto Alfredo Felici, Federico Pesamosca, Anna Ngoc Minh Trang Vu

The paper details the process of developing the ITER Plasma Control System (PCS), that is, how to design and deploy it systematically, in the most efficient and effective manner. The integrated nature of the ITER PCS, with its multitude of coupled control ...

Elsevier Science Sa2024

An Iterative Adaptive Dynamic Programming Approach for Macroscopic Fundamental Diagram-Based Perimeter Control and Route Guidance

Nikolaos Geroliminis

Macroscopic fundamental diagrams (MFDs) have been widely adopted to model the traffic flow of large-scale urban networks. Coupling perimeter control and regional route guidance (PCRG) is a promising strategy to decrease congestion heterogeneity and reduce ...

Informs2024