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

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In two-stage solid-state transformers (SSTs) equipped with LLC DC/DC converters for galvanic isolation, fixed-frequency open-loop operation of LLC stages has been a straightforward and prevailing design choice. Meanwhile, with a closed-loop-operated LLC co ...

This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...

Particle accelerators are the drivers for large-scale research infrastructures for particle physics but also for many branches of condensed matter research. The types of accelerator-driven research infrastructures include particle colliders, neutron, muon ...

This paper introduces a novel method for data-driven robust control of nonlinear systems based on the Koopman operator, utilizing Integral Quadratic Constraints (IQCs). The Koopman operator theory facilitates the linear representation of nonlinear system d ...

The frequency response data of a generalized system is used to design fixed-structure controllers for the H2 and H∞ synthesis problem. The minimization of the two and infinity norm of the transfer function between the exogenous inputs and performance outpu ...

Modern power distribution systems are experiencing a large-scale integration of Converter-Interfaced Distributed Energy Resources (CIDERs). Their presence complicates the analysis and mitigation of harmonics, whose creation and propagation may be amplified ...

The goal of this thesis is to propose pragmatic solutions to real challenges faced in the industry. The scope of this thesis encompasses two subjects: frequency-based structured controller synthesis for linear time-invariant (LTI) systems on one side, and ...

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The work presented in this thesis lies at the intersection of Machine Learning (ML) and control theory. The first part is dedicated to the design of Deep Neural Network (DNN) architectures with specific numerical properties, inspired by dynamical systems m ...

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Macroscopic fundamental diagrams (MFDs) have been widely adopted to model the traffic flow of large-scale urban networks. Coupling perimeter control and regional route guidance (PCRG) is a promising strategy to decrease congestion heterogeneity and reduce ...

A novel approach for robust controller synthesis, which models uncertainty as an elliptical set, is proposed in the paper. Given a set of frequency response functions of linear time-invariant (LTI) multiple-input multiple-output (MIMO) systems, the approac ...

Frequency Response Function (FRF)-based control synthesis methods for Linear Time-Invariant (LTI) systems have been widely used in control theory and industry. Recently, there has been renewed interest in these methods, employing numerical optimization too ...

This work presents a new computational optimization framework for the robust control of parks of Wave Energy Converters (WEC) in irregular waves. The power of WEC parks is maximized with respect to the individual control damping and stiffness coefficients ...

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

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Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Energy-Efficient Particle Accelerators for Research

Koopman-based Data-driven Robust Control of Nonlinear Systems Using Integral Quadratic Constraints

Data-driven fixed-structure frequency-based H2 and H∞ controller design

Unified Harmonic Power-Flow and Stability Analysis of Power Grids with Converter-Interfaced Distributed Energy Resources

Frequency domain data-driven robust and optimal control

Precision luminosity measurement at hadron colliders

Optimizing Dynamic Aperture Studies with Active Learning

Frequency response of fiber reinforced DEAs

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Navigating the Loop: From Control Systems to Neural Networks and Back

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The effect of smooth parametrizations on nonconvex optimization landscapes

An Iterative Adaptive Dynamic Programming Approach for Macroscopic Fundamental Diagram-Based Perimeter Control and Route Guidance

Data-driven IQC-Based Robust Control Design for Hybrid Micro-disturbance Isolation Platform

Achieving Optimal Performance With Data-Driven Frequency-Based Control Synthesis Methods

Robust optimization of control parameters for WEC arrays using stochastic methods