Publications related to Data-Driven Control and Optimization under Noisy and Uncertain Conditions

An Iterative Linear Expansion of Thresholds for l1-based Image Restoration

This paper proposes a novel algorithmic framework to solve image restoration problems under sparsity assumptions. As usual, the reconstructed image is the minimum of an objective functional that consists of a data fidelity term and an l1 regularization. Ho ...

Institute of Electrical and Electronics Engineers2013

Decoupled dq-Current Control of Grid-Tied Voltage Source Converters Using Nonparametric Models

Alfred Rufer, Alireza Karimi, Behrooz Bahrani

This paper presents a vector control strategy for regulating the current of grid-tied voltage source converters (VSCs) in a rotating reference frame. The proposed approach is based on shaping the open-loop and closed-loop transfer matrices of the system. S ...

Institute of Electrical and Electronics Engineers2013

A Multivariable Design Methodology for Voltage Control of a Single-DG-Unit Microgrid

Alfred Rufer, Alireza Karimi, Behrooz Bahrani

This paper proposes a multivariable digital control design methodology for the voltage regulation of an islanded single distributed generation (DG) unit microgrid and its dedicated load. The controller design methodology is based on a family of spectral Mu ...

2013

Plug-and-play distributed state estimation for linear systems

Giancarlo Ferrari Trecate, Marcello Farina

This paper proposes a state estimator for large-scale linear systems described by the interaction of state-coupled subsystems affected by bounded disturbances. We equip each subsystem with a Local State Estimator (LSE) for the reconstruction of the subsyst ...

2013

Plug-and-play distributed state estimation for linear systems

Giancarlo Ferrari Trecate, Marcello Farina

This paper proposes a state estimator for large-scale linear systems described by the interaction of state-coupled subsystems affected by bounded disturbances. We equip each subsystem with a Local State Estimator (LSE) for the reconstruction of the subsyst ...

2013

Iterative Controller Tuning by Real-Time Optimization

Dominique Bonvin, Grégory François, Gene Bunin

The present article looks at the problem of iterative controller tuning, where the parameters of a given controller are adapted in an iterative manner to bring the user-defined performance metric to a local minimum for some repetitive process. Specifically ...

2013

A Real-Time Optimization Framework for the Iterative Controller Tuning Problem

Dominique Bonvin, Grégory François, Gene Bunin

We investigate the general iterative controller tuning (ICT) problem, where the task is to find a set of controller parameters that optimize some user-defined performance metric when the same control task is to be carried out repeatedly. Following a repeat ...

MDPI2013

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

A data-driven approach to mixed-sensitivity control with application to an active suspension system

Alireza Karimi

In this paper, a data-driven approach is proposed to tune fixed-order controllers for unknown stable LTI plants in a mixed-sensitivity loop-shaping framework. The method requires a single set of input-output samples and it is based on convex optimization t ...

Ieee-Inst Electrical Electronics Engineers Inc2013

Learning for Structured Prediction Using Approximate Subgradient Descent with Working Sets

Pascal Fua, Aurélien Lucchi, Yunpeng Li

We propose a working set based approximate subgradient descent algorithm to minimize the margin-sensitive hinge loss arising from the soft constraints in max-margin learning frameworks, such as the structured SVM. We focus on the setting of general graphic ...

2013

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

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An Iterative Linear Expansion of Thresholds for l1-based Image Restoration

Decoupled dq-Current Control of Grid-Tied Voltage Source Converters Using Nonparametric Models

A Multivariable Design Methodology for Voltage Control of a Single-DG-Unit Microgrid

Plug-and-play distributed state estimation for linear systems

Plug-and-play distributed state estimation for linear systems

Iterative Controller Tuning by Real-Time Optimization

A Real-Time Optimization Framework for the Iterative Controller Tuning Problem

Open-loop control of a separated boundary layer

A data-driven approach to mixed-sensitivity control with application to an active suspension system

Learning for Structured Prediction Using Approximate Subgradient Descent with Working Sets

Decoupled dq-Current Control of Grid-Tied Voltage Source Converters Using Nonparametric Models

Iterative Controller Tuning by Real-Time Optimization

A Real-Time Optimization Framework for the Iterative Controller Tuning Problem

An Iterative Linear Expansion of Thresholds for l1-based Image Restoration

A Multivariable Design Methodology for Voltage Control of a Single-DG-Unit Microgrid

Plug-and-play distributed state estimation for linear systems

A data-driven approach to mixed-sensitivity control with application to an active suspension system

Plug-and-play distributed state estimation for linear systems

Open-loop control of a separated boundary layer

Learning for Structured Prediction Using Approximate Subgradient Descent with Working Sets