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

Data-driven LPV Control for Micro-disturbance Rejection in a Hybrid Isolation Platform

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

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

Colin Neil Jones, Bratislav Svetozarevic, Wenjie Xu

We study the problem of performance optimization of closed -loop control systems with unmodeled dynamics. Bayesian optimization (BO) has been demonstrated to be effective for improving closed -loop performance by automatically tuning controller gains or re ...

Elsevier Sci Ltd2024

Data-driven LPV Disturbance Rejection Control with IQC-based Stability Guarantees for Rate-bounded Scheduling Parameter Variations

Alireza Karimi, Elias Sebastian Klauser

In this paper, the challenge of asymptotically rejecting sinusoidal disturbances with unknown time-varying frequency and bounded rate is explored. A novel data-driven approach for designing linear parameter-varying (LPV) con- troller is introduced, leverag ...

2024

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Baiwei Guo

Control systems operating in real-world environments often face disturbances arising from measurement noise and model mismatch. These factors can significantly impact the perfor- mance and safety of the system. In this thesis, we aim to leverage data to de ...

EPFL2023

A combined Control by Interconnection—Model Predictive Control design for constrained Port-Hamiltonian systems

This paper proposes a Control by Interconnection design, for a class of constrained Port-Hamiltonian systems, which is based on an associated Model Predictive Control optimization problem. This associated optimization problem allows to consider both state ...

2022

Stabilization and Accuracy Improvement of Power-Hardware-in-the-Loop Test Using a Robust Data-Driven Method

Alireza Karimi, Seyed Sohail Madani

Power-Hardware-In-the-Loop (PHIL) setups have gained high importance in validation of the performance of newly developed algorithms and devices with low risk and implementation cost. However, the interconnection of a power hardware with a simulated model v ...

2021

Sample Complexity of Linear Quadratic Gaussian (LQG) Control for Output Feedback Systems

Maryam Kamgarpour, Luca Furieri, Na Li

This paper studies a class of partially observed Linear Quadratic Gaussian (LQG) problems with unknown dynamics. We establish an end-to-end sample complexity bound on learning a robust LQG controller for open-loop stable plants. This is achieved using a ro ...

PMLR2021

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

Maryam Kamgarpour, Luca Furieri, Yu Zheng

A convex parameterization of internally stabilizing controllers is fundamental for many controller synthesis procedures. The celebrated Youla parameterization relies on a doubly coprime factorization of the system, while the recent system-level and input-o ...

2021

Shape optimization for a noise reduction problem by non-intrusive parametric reduced modeling

Francesca Bonizzoni, Davide Pradovera

We study a PDE-constrained optimization problem, where the shape and liner material of the nacelle of an aircraft engine are optimized in order to minimize the noise radiated by the engine. More precisely, the acoustic problem is modeled by the Helmholtz e ...

2021

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

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

Graph Chatbot

Chat with Graph Search

Data-driven LPV Control for Micro-disturbance Rejection in a Hybrid Isolation Platform

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

Data-driven LPV Disturbance Rejection Control with IQC-based Stability Guarantees for Rate-bounded Scheduling Parameter Variations

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

A combined Control by Interconnection—Model Predictive Control design for constrained Port-Hamiltonian systems

Stabilization and Accuracy Improvement of Power-Hardware-in-the-Loop Test Using a Robust Data-Driven Method

Sample Complexity of Linear Quadratic Gaussian (LQG) Control for Output Feedback Systems

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

Shape optimization for a noise reduction problem by non-intrusive parametric reduced modeling

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

Sample Complexity of Linear Quadratic Gaussian (LQG) Control for Output Feedback Systems

Stabilization and Accuracy Improvement of Power-Hardware-in-the-Loop Test Using a Robust Data-Driven Method

Data-driven LPV Control for Micro-disturbance Rejection in a Hybrid Isolation Platform

Data-driven LPV Disturbance Rejection Control with IQC-based Stability Guarantees for Rate-bounded Scheduling Parameter Variations

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

A combined Control by Interconnection—Model Predictive Control design for constrained Port-Hamiltonian systems

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

Violation-aware contextual Bayesian optimization for controller performance optimization with unmodeled constraints

Shape optimization for a noise reduction problem by non-intrusive parametric reduced modeling

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