Publications associées à On the Equivalence of Youla, System-Level, and Input-Output Parameterizations

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A novel approach for linear parameter-varying (LPV) controller synthesis for adaptive rejection of time-varying sinusoidal disturbances is proposed. Only the frequency response data of a linear time-invariant (LTI) multiple-input multiple-output (MIMO) sys ...

2024

A convex set of robust D—stabilizing controllers using Cauchy's argument principle

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A new approach is presented to obtain a convex set of robust D—stabilizing fixed structure controllers, relying on Cauchy's argument principle. A convex set of D—stabilizing controllers around an initial D—stabilizing controller for a multi-model set is re ...

Elsevier2022

A first-order primal-dual method with adaptivity to local smoothness

Volkan Cevher, Maria-Luiza Vladarean

We consider the problem of finding a saddle point for the convex-concave objective

\min_x \max_y f(x) + \langle Ax, y\rangle - g^*(y)

, where

f

is a convex function with locally Lipschitz gradient and

g

is convex and possibly non-smooth. We propose an ...

2021

Convex Combination of Diffusion Strategies Over Networks

Ali H. Sayed, Jie Chen

Combining diffusion strategies with complementary properties enables enhanced performance when they can be run simultaneously. In this article, we first propose two schemes for the convex combination of two diffusion strategies, namely, the power-normalize ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2020

System-level, Input-output and New Parameterizations of Stabilizing Controllers, and Their Numerical Computation

Maryam Kamgarpour, Luca Furieri, Na Li

It is known that the set of internally stabilizing controller

\mathcal{C}_{\text{stab}}

is non-convex, but it admits convex characterizations using certain closed-loop maps: a classical result is the {Youla parameterization}, and two recent notions are t ...

2020

First Order Methods For Globally Optimal Distributed Controllers Beyond Quadratic Invariance

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We study the distributed Linear Quadratic Gaussian (LQG) control problem in discrete-time and finite-horizon, where the controller depends linearly on the history of the outputs and it is required to lie in a given subspace, e.g. to possess a certain spars ...

IEEE2020

A data-driven approach to model-reference control with applications to particle accelerator power converters

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A new model-reference data-driven approach is presented which uses the frequency response data of a system in order to avoid the problem of unmodeled dynamics associated with low-order parametric models. It is shown that a convex optimization problem can b ...

PERGAMON-ELSEVIER SCIENCE LTD2019

Robust control of systems with sector nonlinearities via convex optimization: A data-driven approach

Alireza Karimi, Achille Nicoletti

In this paper, a new data-driven method for designing robust controllers is proposed for systemswith sector-bounded nonlinearities and multimodel uncertainties. The results from the circle criterion are used to generate necessary and sufficient convex cons ...

WILEY2019

An Input–Output Parametrization of Stabilizing Controllers: Amidst Youla and System Level Synthesis

Maryam Kamgarpour, Luca Furieri

This letter proposes a novel input-output parametrization of the set of internally stabilizing output-feedback controllers for linear time invariant (LTI) systems. Our underlying idea is to directly treat the closed-loop transfer matrices from disturbances ...

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A Data-Driven Method for Computing Fixed-Structure Low-Order Controllers With H-infinity Performance

Alireza Karimi, Achille Nicoletti

Recently, a new data-driven method for robust control with H-infinity performance has been proposed. This method is based on convex optimization and converges to the optimal performance when the controller order increases. However, for low-order controller ...

IEEE2018

On the Equivalence of Youla, System-Level, and Input-Output Parameterizations

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A convex set of robust D—stabilizing controllers using Cauchy's argument principle

A first-order primal-dual method with adaptivity to local smoothness

Convex Combination of Diffusion Strategies Over Networks

System-level, Input-output and New Parameterizations of Stabilizing Controllers, and Their Numerical Computation

First Order Methods For Globally Optimal Distributed Controllers Beyond Quadratic Invariance

A data-driven approach to model-reference control with applications to particle accelerator power converters

Robust control of systems with sector nonlinearities via convex optimization: A data-driven approach

An Input–Output Parametrization of Stabilizing Controllers: Amidst Youla and System Level Synthesis

A Data-Driven Method for Computing Fixed-Structure Low-Order Controllers With H-infinity Performance

A first-order primal-dual method with adaptivity to local smoothness

System-level, Input-output and New Parameterizations of Stabilizing Controllers, and Their Numerical Computation

A convex set of robust D—stabilizing controllers using Cauchy's argument principle

Convex Combination of Diffusion Strategies Over Networks

Robust control of systems with sector nonlinearities via convex optimization: A data-driven approach

A Data-Driven Method for Computing Fixed-Structure Low-Order Controllers With H-infinity Performance

A data-driven approach to model-reference control with applications to particle accelerator power converters

An Input–Output Parametrization of Stabilizing Controllers: Amidst Youla and System Level Synthesis

First Order Methods For Globally Optimal Distributed Controllers Beyond Quadratic Invariance