Publications related to Robust stability properties of soft constrained MPC

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

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

Alireza Karimi, Elias Sebastian Klauser

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

Critical degeneracy in a nonlinear hyperbolic equation can produce atypical instability

This paper deals with the initial value problem for a semilinear wave equation on a bounded domain and solutions are required to vanish on the boundary of this domain. The essential feature of the situation considered here is that the ellipticity of the sp ...

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

Homothetic Tube Model Predictive Control With Multi-Step Predictors

Giancarlo Ferrari Trecate, Danilo Saccani, Melanie Nicole Zeilinger

We present a robust model predictive control (MPC) framework for linear systems facing bounded parametric uncertainty and bounded disturbances. Our approach deviates from standard MPC formulations by integrating multi-step predictors, which provide reduced ...

Piscataway2023

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

Nonlinear Transient Stability Analysis of Phased-Locked Loop Based Grid-Following Voltage Source Converters Using Lyapunov’s Direct Method

Alireza Karimi, Behrooz Bahrani

In this paper, using Lyapunov’s stability theorem, the transient stability conditions for a grid-following Voltage Source Converter (VSC) are found. These conditions take into account both the grid specifications and the VSC’s dynamics. The derived conditi ...

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 stability properties of soft constrained MPC

Graph Chatbot

Chat with Graph Search

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

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

Critical degeneracy in a nonlinear hyperbolic equation can produce atypical instability

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Homothetic Tube Model Predictive Control With Multi-Step Predictors

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

Nonlinear Transient Stability Analysis of Phased-Locked Loop Based Grid-Following Voltage Source Converters Using Lyapunov’s Direct 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

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

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

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Critical degeneracy in a nonlinear hyperbolic equation can produce atypical instability

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

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

Nonlinear Transient Stability Analysis of Phased-Locked Loop Based Grid-Following Voltage Source Converters Using Lyapunov’s Direct Method

Homothetic Tube Model Predictive Control With Multi-Step Predictors