Publications related to Data-driven Methods for Control: from Linear to Lifting

Stability and Performance Verification of Optimization-based Controllers

This paper presents a method to verify closed-loop properties of optimization-based controllers for deterministic and stochastic constrained polynomial discrete-time dynamical systems. The closed-loop properties amenable to the proposed technique include g ...

2015

The control of the scaled false discovery rate, a flexible and comprehensive error control and a powerful theoretical tool in multiple testing

Dimitri Nestor Alice Van De Ville, Stephan Morgenthaler, Djalel Eddine Meskaldji

Given the large number of papers written over the last ten years on error controls in high dimensional multiple testing, it would be worthwhile to consider a single comprehensive technique that allows user flexibility in error control when dealing with big ...

2015

A comparison of model-based and data-driven controller tuning

Alireza Karimi, Klaske van Heusden

In many industrial applications, finding a model from physical laws that is both simple and reliable for control design is a hard and time-consuming undertaking. When a set of input/output measurements is available, one can derive the controller directly f ...

Wiley-Blackwell2014

Enhancing statistical performance of data-driven controller tuning via L2-regularization

Alireza Karimi

Noniterative data-driven techniques are design methods that allow optimal feedback control laws to be derived from input-output (I/O) data only, without the need of a model of the process. A drawback of these methods is that, in their standard formulation, ...

Pergamon-Elsevier Science Ltd2014

Open-loop control of a separated boundary layer

François Gallaire, Edouard Boujo

Linear optimal gains

G_{opt}(\omega)

are computed for the separated boundary-layer flow past a two-dimensional bump in the subcritical regime. Very large values are found, making it possible for small-amplitude noise to be strongly amplified and to desta ...

Elsevier France-Editions Scientifiques Medicales Elsevier2014

Offset-Free Output Feedback Predictive Control for Longitudinal Beam Dynamics in Heavy Ion Synchrotrons

Timm Faulwasser

Control of the longitudinal beam dynamics in heavy ion synchrotrons is a challenging task due primarily to the very fast time constants present in the system. Recently, the authors developed a model predictive controller for this system and demonstrated th ...

2014

A parametric multi-convex splitting technique with application to real-time NMPC

Colin Neil Jones, Jean-Hubert Hours

A novel splitting scheme to solve parametric multi-convex programs is presented. It consists of a fixed number of proximal alternating minimisations and a dual update per time step, which makes it attractive in a real-time Nonlinear Model Predictive Contro ...

2014

Model-based and data-driven model-reference control: a comparative analysis

Alireza Karimi, Klaske van Heusden

In many industrial applications, finding a model from physical laws that is both simple and reliable for control design is a hard and time-consuming undertaking. When a set of input/output (I/O) measurements is available, one can derive the controller dire ...

2013

Geometric Variational Models for Inverse Problems in Imaging

Virginia Estellers Casas

This dissertation develops geometric variational models for different inverse problems in imaging that are ill-posed, designing at the same time efficient numerical algorithms to compute their solutions. Variational methods solve inverse problems by the fo ...

EPFL2013

Open-loop control of a separated boundary layer

François Gallaire, Edouard Boujo

Linear optimal gains

G_opt(\omega)

are computed for the separated boundary-layer flow past a two-dimensional bump in the subcritical regime. Very large values are found, making it possible for small-amplitude noise to be strongly amplified and to destabi ...

Cépaduès Editions2013

Data-driven Methods for Control: from Linear to Lifting

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Stability and Performance Verification of Optimization-based Controllers

The control of the scaled false discovery rate, a flexible and comprehensive error control and a powerful theoretical tool in multiple testing

A comparison of model-based and data-driven controller tuning

Enhancing statistical performance of data-driven controller tuning via L2-regularization

Open-loop control of a separated boundary layer

Offset-Free Output Feedback Predictive Control for Longitudinal Beam Dynamics in Heavy Ion Synchrotrons

A parametric multi-convex splitting technique with application to real-time NMPC

Model-based and data-driven model-reference control: a comparative analysis

Geometric Variational Models for Inverse Problems in Imaging

Open-loop control of a separated boundary layer

Enhancing statistical performance of data-driven controller tuning via L2-regularization

Open-loop control of a separated boundary layer

Offset-Free Output Feedback Predictive Control for Longitudinal Beam Dynamics in Heavy Ion Synchrotrons

A parametric multi-convex splitting technique with application to real-time NMPC

The control of the scaled false discovery rate, a flexible and comprehensive error control and a powerful theoretical tool in multiple testing

Stability and Performance Verification of Optimization-based Controllers

A comparison of model-based and data-driven controller tuning

Geometric Variational Models for Inverse Problems in Imaging

Open-loop control of a separated boundary layer

Model-based and data-driven model-reference control: a comparative analysis