Publications related to H∞ Controller Design for Spectral MIMO Models by Convex Optimization

Preserving the positivity of the deformation gradient determinant in intergrid interpolation by combining RBFs and SVD: Application to cardiac electromechanics

The accurate, robust and efficient transfer of the deformation gradient tensor between meshes of different resolution is crucial in cardiac electromechanics simulations. This paper presents a novel method that combines rescaled localized Radial Basis Funct ...

Lausanne2023

Unified Green's function approach for spectral and thermodynamic properties from algorithmic inversion of dynamical potentials

Nicola Marzari, Tommaso Chiarotti, Andrea Ferretti

Dynamical potentials appear in many advanced electronic-structure methods, including self-energies from many-body perturbation theory, dynamical mean-field theory, electronic-transport formulations, and many embedding approaches. Here, we propose a novel t ...

AMER PHYSICAL SOC2022

Testing For The Rank Of A Covariance Operator

Victor Panaretos

How can we discern whether the covariance operator of a stochastic pro-cess is of reduced rank, and if so, what its precise rank is? And how can we do so at a given level of confidence? This question is central to a great deal of methods for functional dat ...

INST MATHEMATICAL STATISTICS-IMS2022

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

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

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

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

Kernel methods and Model predictive approaches for Learning and Control

Sanket Sanjay Diwale

Data-driven modeling and feedback control play a vital role in several application areas ranging from robotics, control theory, manufacturing to management of assets, financial portfolios and supply chains. Many such problems in one way or another are rela ...

EPFL2019

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

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

H∞ Controller Design for Spectral MIMO Models by Convex Optimization

Graph Chatbot

Chat with Graph Search

Preserving the positivity of the deformation gradient determinant in intergrid interpolation by combining RBFs and SVD: Application to cardiac electromechanics

Unified Green's function approach for spectral and thermodynamic properties from algorithmic inversion of dynamical potentials

Testing For The Rank Of A Covariance Operator

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

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

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

Kernel methods and Model predictive approaches for Learning and Control

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

Preserving the positivity of the deformation gradient determinant in intergrid interpolation by combining RBFs and SVD: Application to cardiac electromechanics

Testing For The Rank Of A Covariance Operator

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

Kernel methods and Model predictive approaches for Learning and Control

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

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

Unified Green's function approach for spectral and thermodynamic properties from algorithmic inversion of dynamical potentials

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

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