Publications related to A Data-Driven Approach to Power Converter Control via Convex Optimization

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

Gabor dual windows using convex optimization

Nathanaël Perraudin

Redundant Gabor frames admit an infinite number of dual frames, yet only the canonical dual Gabor system, con- structed from the minimal l2-norm dual window, is widely used. This window function however, might lack desirable properties, such as good time-f ...

2013

Adaptive stochastic convex optimization over networks

Ali H. Sayed

In this work, we study the task of distributed optimization over a network of learners in which each learner possesses a convex cost function, a set of affine equality constraints, and a set of convex inequality constraints. We propose a distributed diffus ...

IEEE2013

Direct data-driven design of sparse controllers

Alireza Karimi

This paper deals with direct data-driven design of model-reference controllers whose number of parameters is constrained. Input-output (I/O) sparse controllers are introduced and proposed as an alternative to low-order controller tuning. The optimal I/O sp ...

IEEE2013

l0-deconvolution for compressive diffusion MRI

Jean-Philippe Thiran, Yves Wiaux, Alessandro Daducci, Anna Auria Rasclosa

Diffusion MRI is a well established imaging modality providing a powerful way to non-invasively probe the structure of the white matter. Despite the potential of the technique, the intrinsic long scan times of these sequences have hampered their use in cli ...

2013

To Convexify or Not? Regression with Clustering Penalties on Graphs

Volkan Cevher, Luca Baldassarre, Marwa El Halabi

We consider minimization problems that are compositions of convex functions of a vector

\x \in\reals^N

with submodular set functions of its support (i.e., indices of the non-zero coefficients of

\x

). Such problems are in general difficult for large

N

...

IEEE2013

A solution to the flexible transmission benchmark by convex optimization

Alireza Karimi, Gorka Galdos Sanz de Galdeano

The flexible transmission benchmark was proposed in the European Journal of Control to evaluate some robust digital control approaches in 1995. With progress in convex optimization algorithms new methods for robust controller design are developed. A recent ...

SAGE Publications2012

Regularized Bundle Methods for Convex and Non-Convex Risks

Machine learning is most often cast as an optimization problem. Ideally, one expects a convex objective function to rely on efficient convex optimizers with nice guarantees such as no local optima. Yet, non-convexity is very frequent in practice and it may ...

2012

A toolbox for robust PID controller tuning using convex optimization

Alireza Karimi, Vinicius De Oliveira, Mehdi Sadeghpour

A robust PID controller design toolbox for Matlab is presented in this paper. The design is based on linearizing or convexifying the conventional non-convex constraints on the classical robustness margins or H∞ constraints. Then the existing optimization s ...

2012

Data-driven model reference control with asymptotically guaranteed stability

Dominique Bonvin, Alireza Karimi, Klaske van Heusden

This paper presents a data-driven controller tuning method that includes a set of constraints for ensuring closed-loop stability. The approach requires a single experiment and can also be applied to nonminimum-phase or unstable systems. The tuning scheme u ...

Wiley-Blackwell2011

A Data-Driven Approach to Power Converter Control via Convex Optimization

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

Gabor dual windows using convex optimization

Adaptive stochastic convex optimization over networks

Direct data-driven design of sparse controllers

l0-deconvolution for compressive diffusion MRI

To Convexify or Not? Regression with Clustering Penalties on Graphs

A solution to the flexible transmission benchmark by convex optimization

Regularized Bundle Methods for Convex and Non-Convex Risks

A toolbox for robust PID controller tuning using convex optimization

Data-driven model reference control with asymptotically guaranteed stability

Regularized Bundle Methods for Convex and Non-Convex Risks

Direct data-driven design of sparse controllers

l0-deconvolution for compressive diffusion MRI

To Convexify or Not? Regression with Clustering Penalties on Graphs

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

Gabor dual windows using convex optimization

Adaptive stochastic convex optimization over networks

A solution to the flexible transmission benchmark by convex optimization

A toolbox for robust PID controller tuning using convex optimization

Data-driven model reference control with asymptotically guaranteed stability