Publications associées à Adaptive Disturbance Rejection with Data-driven LPV Control for Hybrid Microvibration Isolation Systems

Publications associées (9)

Brunovsky Riccati Recursion for Linear Model Predictive Control

In almost all algorithms for Model Predictive Control (MPC), the most time-consuming step is to solve some form of Linear Quadratic (LQ) Optimal Control Problem (OCP) repeatedly. The commonly recognized best option for this is a Riccati recursion based sol ...

IEEE2025

On GIT stability of linear systems of hypersurfaces in projective spaces

Aline Zanardini

In this paper, we consider the problem of classifying linear systems of hypersurfaces (of a fixed degree) in projective space up to projective equivalence. Our main result consists of a complete criterion for (semi)stability in the sense of geometric invar ...

2025

Neural Distributed Controllers with Port-Hamiltonian Structures

Giancarlo Ferrari Trecate, Muhammad Zakwan

Controlling large-scale cyber-physical systems necessitates optimal distributed policies, relying solely on local real-time data and limited communication with neighboring agents. However, finding optimal controllers remains challenging, even in seemingly ...

Institute of Electrical and Electronics Engineers Inc.2024

Near-Optimal Design of Safe Output-Feedback Controllers From Noisy Data

Giancarlo Ferrari Trecate, Luca Furieri, Baiwei Guo, Andrea Martin

As we transition toward the deployment of data-driven controllers for black-box cyberphysical systems, complying with hard safety constraints becomes a primary concern. Two key aspects should be addressed when input-output data are corrupted by noise: how ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Stability Verification of Neural Network Controllers using Mixed-Integer Programming

Colin Neil Jones, Daniel Kuhn, Roland Schwan

We propose a framework for the stability verification of Mixed-Integer Linear Programming (MILP) representable control policies. This framework compares a fixed candidate policy, which admits an efficient parameterization and can be evaluated at a low comp ...

2023

Modeling noise experiments performed at AKR-2 and CROCUS zero-power reactors

Vincent Pierre Lamirand, Mathieu Hursin

CORTEX is a EU H2020 project (2017-2021) devoted to the analysis of 'reactor neutron noise' in nuclear reactors, i.e. the small fluctuations occurring around the stationary state due to external or internal disturbances in the core. One important aspect of ...

2023

Optimum trajectory learning in musculoskeletal systems with model predictive control and deep reinforcement learning

Henry Markram, Marc-Oliver Gewaltig

From the computational point of view, musculoskeletal control is the problem of controlling high degrees of freedom and dynamic multi-body system that is driven by redundant muscle units. A critical challenge in the control perspective of skeletal joints w ...

2022

Distributed model predictive control of buildings and energy hubs

Colin Neil Jones

Model predictive control (MPC) strategies can be applied to the coordination of energy hubs to reduce their energy consumption. Despite the effectiveness of these techniques, their potential for energy savings are potentially underutilized due to the fact ...

ELSEVIER SCIENCE SA2022

LTP Modeling and Analysis of Frequency Coupling in PLL-Synchronized Converters for Harmonic Power Flow Studies

Mario Paolone, Yihui Zuo, Johanna Kristin Maria Becker

As known, nonlinear loads in power systems originate harmonic distortion and power quality issues. Converter-interfaced loads exhibit a nonlinear behaviour as well and may largely contribute to increase the harmonic pollution. The nonlinearities introduced ...

2022