Giancarlo Ferrari Trecate

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Voltage and frequency control in an islanded ac microgrid (ImG) amounts to stabilizing an a priori unknown ImG equilibrium induced by loads and changes in topology. This article puts forth a unified control framework, which, while guaranteeing such stabili ...

This article describes a control approach for large-scale electricity networks, with the goal of efficiently coordinating distributed generators to balance unexpected load variations with respect to nominal forecasts. To mitigate the difficulties due to th ...

In this paper, we propose a suboptimal distributed LQR control method, applicable to systems coupled through both physical interconnections and the quadratic cost to be minimized. Thanks to a novel suboptimal but distributed cost-to-go matrix update that e ...

This paper characterizes a new parametrization of nonlinear networked incrementally L2 -bounded operators in discrete time. The distinctive novelty is that our parametrization is free - that is, a sparse large-scale operator with bounded incremental L2 gai ...

This paper proposes a novel learning-based approach for achieving exponential stabilization of nonlinear control-affine systems. We leverage the Control Contraction Metrics (CCMs) framework to co-synthesize Neural Contraction Metrics (NCMs) and Neural Netw ...

Recent work in data-driven control has revived behavioral theory to perform a variety of complex control tasks, by directly plugging libraries of past input-output trajectories into optimal control problems. Despite recent advances, a key aspect remains un ...

We consider the application of passivity theory to the problem of voltage stabilization in DC microgrids (DCmGs) given by the interconnection of Distributed Generation Units (DGUs), dynamic RL lines, and loads. We first provide a novel result on stable int ...

This paper performs an extensive review on control schemes and architectures applied to dc microgrids (MGs). It covers multilayer hierarchical control schemes, coordinated control strategies, plug-and-play operations, stability and active damping aspects, ...

The problem of replay attacks in the communication network between Distributed Generation Units (DGUs) of a DC microgrid is examined. The DGUs are regulated through a hierarchical control architecture, and are networked to achieve secondary control objecti ...

To solve unmodeled optimization problems with hard constraints, this paper proposes a novel zeroth-order approach called Safe Zeroth-order Optimization using Linear Programs (SZO-LP). The SZO-LP method solves a linear program in each iteration to find a de ...

Consensusability is an important property for many multi-agent systems (MASs) as it implies the existence of networked controllers driving the states of MAS subsystems to the same value. Consensusability is of interest even when the MAS subsystems are phys ...

Unknown-input observers (UIOs) allow for estimation of the states of an LTI system without knowledge of all inputs. In this letter, we provide a novel data-driven UIO based on behavioral system theory and the result known as Fundamental Lemma proposed by J ...

In this paper, we address the problem of synthesizing decentralized current controllers for grid-feeding converters of current-controlled distributed generation units (CDGUs) in dc microgrids (MGs). Notably, a plug-and-play (PnP) design procedure is propos ...

Deep Neural Networks (DNNs) training can be difficult due to vanishing and exploding gradients during weight optimization through backpropagation. To address this problem, we propose a general class of Hamiltonian DNNs (H-DNNs) that stem from the discretiz ...

The paper considers the problem of detecting cyber-attacks occurring in communication networks typically used in the secondary control layer of DC microgrids. The proposed distributed methodology allows for scalable monitoring of a microgrid and is able to ...

In this technical article, we analyze the performance improvement and optimality properties of the learning model predictive control (LMPC) strategy for linear deterministic systems. The LMPC framework is a policy iteration scheme where closed-loop traject ...

Reliable integration and operation of renewable distributed energy resources requires accurate distribution grid models. However, obtaining precise models by field inspection is often prohibitively expensive, given their large scale and the ongoing nature ...

We consider the application of passivity theory to the problem of voltage stabilization in DC microgrids, which are composed of distributed generation units, dynamic RLC lines, and nonlinear ZIP (constant impedance, constant current, and constant power) lo ...

The increasing integration of intermittent renewable generation, especially at the distribution level, necessitates advanced planning and optimisation methodologies contingent on the knowledge of the admittance matrix, capturing the topology and line param ...

Ride-sourcing system can provide passengers with fast and efficient service with a fleet of vehicles, while asymmetry between origin and destination distributions of trips, nonuniform passenger's demand for rides in different districts creates imbalances i ...

Giancarlo Ferrari Trecate

Chattez avec Graph Search

A Unified Passivity-Based Framework for Control of Modular Islanded AC Microgrids

Supervised model predictive control of large-scale electricity networks via clustering methods

Suboptimal Distributed LQR Design for Physically Coupled Systems

Unconstrained Learning of Networked Nonlinear Systems via Free Parametrization of Stable Interconnected Operators

Neural Exponential Stabilization of Control-affine Nonlinear Systems

A Behavioral Input-Output Parametrization of Control Policies with Suboptimality Guarantees

A Passivity-Based Approach to Voltage Stabilization in DC Microgrids

Review on Control of DC Microgrids

Distributed watermarking for secure control of microgrids under replay attacks

Safe Zeroth-Order Optimization Using Linear Programs

Consensusability of linear interconnected multi-agent systems

Data-Driven Unknown-Input Observers and State Estimation

Plug-and-play design of current controllers for grid-feeding converters in DC microgrids

Hamiltonian Deep Neural Networks Guaranteeing Non-Vanishing Gradients by Design

Distributed Cyber-Attack Detection in the Secondary Control of DC Microgrids

On the Optimality and Convergence Properties of the Iterative Learning Model Predictive Controller

Power grid parameter estimation without phase measurements: Theory and empirical validation

A Passivity-Based Approach to Voltage Stabilization in DC Microgrids with ZIP loads

Bayesian Methods for the Identification of Distribution Networks

Idle-vehicle Rebalancing Coverage Control for Ride-sourcing systems