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

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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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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 ...

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

Chattez avec Graph Search

Brunovsky Riccati Recursion for Linear Model Predictive Control

On GIT stability of linear systems of hypersurfaces in projective spaces

Neural Distributed Controllers with Port-Hamiltonian Structures

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

Stability Verification of Neural Network Controllers using Mixed-Integer Programming

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

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

Distributed model predictive control of buildings and energy hubs

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