Publications by Achille Nicoletti

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

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

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

Alireza Karimi, Achille Nicoletti, Michele Martino

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

A Robust Data-Driven Controller Design Methodology With Applications to Particle Accelerator Power Converters

Alireza Karimi, Achille Nicoletti, Michele Martino

A new data-driven approach using the frequency response function (FRF) of a system is proposed for designing robust-fixed structure digital controllers for particle accelerators' power converters. This design method ensures that the dynamics of a system ar ...

2019

Robust H-infinity Controller Design Using Frequency-Domain Data via Convex Optimization

Alireza Karimi, Yuanming Zhu, Achille Nicoletti

A new robust controller design method that satisfies the H-infinity criterion is developed for linear time-invariant single-input single-output (SISO) systems. A data-driven approach is implemented in order to avoid the unmodeled dynamics associated with p ...

Wiley-Blackwell2018

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

Alireza Karimi, Achille Nicoletti

Recently, a new data-driven method for robust control with H∞ 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 controllers, the p ...

Elsevier2018

Robust Controller Design For Linear Systems With Nonlinear Distortions: A Data-Driven Approach

Alireza Karimi, Achille Nicoletti

The extensive use of frequency-domain tools for analyzing and controlling linear systems have become indispensable for the control systems engineer. However, due to the increased performance demands on today's industrial systems, the effects of certain non ...

Elsevier2018

A Data-Driven Frequency-Domain Approach for Robust Controller Design via Convex Optimization

Achille Nicoletti

The objective of this dissertation is to develop data-driven frequency-domain methods for designing robust controllers through the use of convex optimization algorithms. Many of today's industrial processes are becoming more complex, and modeling accurate ...

EPFL2018

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

Alireza Karimi, Achille Nicoletti, Michele Martino

A new model reference data-driven approach is presented for synthesizing controllers for the CERN power converter control system. This method uses the frequency re- sponse function (FRF) of a system in order to avoid the problem of unmodeled dynamics assoc ...

2017

A Data-Driven Approach in Designing RST Controllers with H∞ Performance via Convex Optimization

Alireza Karimi, Zlatko Emedi, Achille Nicoletti

In this paper, a new method for designing robust fixed-order

\mathcal{H}_{\infty}

discrete-time controllers is presented. The controller structure is a two-degree of freedom polynomial controller of the

RST

type. A data-driven approach is implemented f ...

IEEE2015

H∞ smith predictor design for time-delayed MIMO systems via convex optimization

Alireza Karimi, Achille Nicoletti

A new method for robust fixed-order H∞ controller design for uncertain time-delayed MIMO systems is presented. It is shown that the H∞ robust performance condition can be represented by a set of convex constraints with respect to the parameters of a linear ...

IEEE2014