Michele Cucuzzella

SY
5papers
341citations
Novelty41%
AI Score24

5 Papers

OCApr 29, 2018
A Robust Consensus Algorithm for Current Sharing and Voltage Regulation in DC Microgrids

Michele Cucuzzella, Sebastian Trip, Claudio De Persis et al.

In this paper a novel distributed control algorithm for current sharing and voltage regulation in Direct Current (DC) microgrids is proposed. The DC microgrid is composed of several Distributed Generation units (DGUs), including Buck converters and current loads. The considered model permits an arbitrary network topology and is affected by unknown load demand and modelling uncertainties. The proposed control strategy exploits a communication network to achieve proportional current sharing using a consensus-like algorithm. Voltage regulation is achieved by constraining the system to a suitable manifold. Two robust control strategies of Sliding Mode (SM) type are developed to reach the desired manifold in a finite time. The proposed control scheme is formally analyzed, proving the achievement of proportional current sharing, while guaranteeing that the weighted average voltage of the microgrid is identical to the weighted average of the voltage references.

SYMar 2, 2020
Differentiation and Passivity for Control of Brayton-Moser Systems

Krishna Chaitanya Kosaraju, Michele Cucuzzella, Jacquelien M. A. Scherpen et al.

This paper deals with a class of Resistive-Inductive-Capacitive (RLC) circuits and switched RLC (s-RLC) circuits modeled in Brayton Moser framework. For this class of systems, new passivity properties using a Krasovskii's type Lyapunov function as storage function are presented. Consequently, the supply-rate is a function of the system states, inputs and their first time-derivatives. Moreover, after showing the integrability property of the port-variables, two simple control methodologies called output shaping and input shaping are proposed for regulating the voltage in RLC and s-RLC circuits. Global asymptotic convergence to the desired operating point is theoretically proved for both proposed control methodologies. Moreover, robustness with respect to load uncertainty is ensured by the input shaping methodology. The applicability of the proposed methodologies is illustrated by designing voltage controllers for DC-DC converters and DC networks.

SYMar 4, 2019
Robust Passivity-Based Control of Boost Converters in DC Microgrids

Michele Cucuzzella, Riccardo Lazzari, Yu Kawano et al.

This work deals with the design of a robust and decentralized passivity-based control scheme for regulating the voltage of a DC microgrid through boost converters. A Krasovskii-type storage function is proposed and a (local) passivity property for DC microgrids comprising unknown 'ZIP' (constant impedance 'Z', constant current 'I' and constant power 'P') loads is established. More precisely, the input port-variable of the corresponding passive map is equal to the first-time derivative of the control input. Then, the integrated input port-variable is used to shape the closed loop storage function such that it has a minimum at the desired equilibrium point. Convergence to the desired equilibrium is theoretically analyzed and the proposed control scheme is validated through experiments on a real DC microgrid.

SYNov 18, 2022
Optimal service station design for traffic mitigation via genetic algorithm and neural network

Carlo Cenedese, Michele Cucuzzella, Adriano Cotta Ramusino et al.

This paper analyzes how the presence of service stations on highways affects traffic congestion. We focus on the problem of optimally designing a service station to achieve beneficial effects in terms of total traffic congestion and peak traffic reduction. Microsimulators cannot be used for this task due to their computational inefficiency. We propose a genetic algorithm based on the recently proposed CTMs, that efficiently describes the dynamics of a service station. Then, we leverage the algorithm to train a neural network capable of solving the same problem, avoiding implementing the CTMs. Finally, we examine two case studies to validate the capabilities and performance of our algorithms. In these simulations, we use real data extracted from Dutch highways.

SYSep 5, 2017
Passivity based design of sliding modes for optimal Load Frequency Control

Sebastian Trip, Michele Cucuzzella, Claudio De Persis et al.

This paper proposes a distributed sliding mode control strategy for optimal Load Frequency Control (OLFC) in power networks, where besides frequency regulation also minimization of generation costs is achieved (economic dispatch). We study a nonlinear power network partitioned into control areas, where each area is modelled by an equivalent generator including voltage and second order turbine-governor dynamics. The turbine-governor dynamics suggest the design of a sliding manifold, such that the turbine-governor system enjoys a suitable passivity property, once the sliding manifold is attained. This work offers a new perspective on OLFC by means of sliding mode control, and in comparison with existing literature, we relax required dissipation conditions on the generation side and assumptions on the system parameters.