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IEEE/ACM 7th International Conference on Utility and Cloud Computing (UCC)

作者： Leva, Alberto Mastrandrea, Daniele Bonvini, Marco Papadopoulos, Alessandro Vittorio Politecn Milan DEIB Milan Italy Lawrence Berkeley Natl Lab Berkeley CA USA Lund Univ Dept Automat Control S-22100 Lund Sweden

ISBN: (纸本)9781479978816

Cloud computing has recently received considerable attention, as a promising approach for delivering ICT services by improving the utilisation of data centre resources. On the other hand, the increased usage of ICT, jointly with the increased cost of energy, make designing and managing data centres with energy efficient strategies a crucial and strategical problem. In the literature there are many studies based on Computational Fluid Dynamics (CFD) simulation models. While the obtained results are usually very reliable and accurate, the massive use of such models for control design require a large amount of time due to their computational complexity and scarce flexibility. In addition, CFD models are usually quite sensitive to any kind of change to the operating conditions, e.g. when varying the considered load balancing algorithm. In this paper, we propose a modelling and simulation framework suited for control design, that is able to simulate both heating and energy phenomena, and different load balancing strategies in a data centre. The purpose of this work is to provide a tool to perform energy-efficiency targeted studies, providing accurate and reliable results.

关键词： Data Centres Energy Optimisation object-oriented modelling and simulation

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Ensuring consistency in scalable-detail models for DT-based control 17th

Ensuring consistency in scalable-detail models for DT-based ...

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17th IFAC Symposium on Information Control Problems in Manufacturing (INCOM)

作者： Cimino, Chiara Leva, Alberto Ferretti, Gianni Politecn Milan DEIB Milan Italy

Digital Twins (DTs for short) are a powerful aid for creating, assessing and maintaining control strategies. This use of DTs however requires that the physical entities to control be described at different levels of detail. For example, simple I/O models are used to compute parameters of modulating controllers, more time-accurate ones may be required to set up and assess logic controls, high-accuracy, possibly nonlinear ones may serve for overall strategy verification, and for software-in-the-loop testing, also the host computing/network architecture needs representing. In such a complex scenario, guaranteeing that all the descriptions of all elements are consistent with one another is a relevant problem. We discuss this matter and propose a solution, in the form of a modelling paradigm where as a novel contributions relationships (in a sense analogous to what the term means in database theory) can be instated and enforced. This allows to create and maintain knowledge based made of interrelate data and models, embracing all the major DT interpretations proposed so far in the literature, or said more explicitly, combining data-driven and model-driven DTs in a single framework. We also provide an illustrative example. Copyright (C) 2021 The Authors.

关键词： Digital Twins Advanced manufacturing Cyber-Physical Systems Industrial automation object-oriented modelling and simulation

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An integrated simulation paradigm for lifecycle-covering maintenance in the Industry 4.0 context 4

An integrated simulation paradigm for lifecycle-covering mai...

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4th International-Federation-of-Automatic-Control (IFAC) Workshop on Advanced Maintenance Engineering, Services and Technologies (AMEST)

作者： Cimino, Chiara Leva, Alberto Negri, Elisa Macchi, Marco Politecn Milan DEIB Milan Italy Politecn Milan DIG Milan Italy

The Industry 4.0 is pushing a fast evolution in all manufacturing operations under heterogeneous aspects. Maintenance, in all its numerous declinations along the life cycle of a production asset, is no exception. A myriad of decisions need taking-often on short time horizons, involving different physical and technological domains, and with limited knowledge available. A myriad of data sources need exploiting and interpreting-often poorly structured, requiring reconciliation, and affected by uncertainty. A lot of tools are therefore used-each one conceived for a specific purpose, often leveraging knowledge drawn from different cultures, and dealing with production assets' models that are hard to integrate with one another. We conjecture that the OOMS (object-oriented modelling and simulation) paradigm can help address such a tough scenario. In this paper we structure and motivate the statement just made, provide high-level supporting examples, and outline future work as for both research and technology. Copyright (C) 2020 The Authors.

关键词： modelling and simulation for maintenance Advanced manufacturing Cyber-Physical Systems Dynamic models First-principle models object-oriented modelling and simulation

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The role of dynamics in digital twins and its problem-tailored representation 21st

The role of dynamics in digital twins and its problem-tailor...

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21st IFAC World Congress on Automatic Control - Meeting Societal Challenges

作者： Cimino, Chiara Ferretti, Gianni Leva, Alberto Politecn Milan DEIB Milan Italy

In Smart Manufacturing, the Internet of Things technology brings about new possibilities as for the interaction of Cyber-Physical Systems with their virtual models in Industry 4.0 jargon, Digital Twins. Besides traditional roles in engineering and control design, Digital Twins cab play innovative ones by evolving together with their cyber-physical counterpart: predictive maintenance, fault detection, or fast training of data-based decision aid tools. In this paper we focus on the relevance of dynamic models in this scenario, particularly as for the co-existence of continuous-time and discrete-event models wherever control and planning are involved. We argue that in such cases, models with analysis-specific levels of detail have to co-exist, interact and maintain mutual consistency. We propose a modelling approach to address the problem, and present a supporting example based on an object-oriented modelling language. Copyright (C) 2020 The Authors.

关键词： Dynamic models Advanced manufacturing Production control and management Cyber-physical systems object-oriented modelling and simulation

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A multi-domain modelling and verification procedure within MBSE approach to design propulsion systems for road electric vehicles

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MECHANICS & INDUSTRY 2017年第1期18卷

作者： Capasso, Clemente Hammadi, Moncef Patalano, Stanislao Renaud, Ruixian Veneri, Ottorino CNR Natl Res Council Italy Ist Motori Via Marconi 4 I-80125 Naples Italy Higher Inst Mech Engn SUPMECA Paris 3 Rue Fernand Hainaut F-93407 St Ouen France Univ Naples Federico II Dept Ind Engn Ple V Tecchio 80 I-80125 Naples Italy

The paper deals with the model based systems engineering (MBSE) approach, focused on the designing process of propulsion systems for road electric vehicles. In particular, the paper adopts multidomain modelling, in accordance with a top-down approach. The process, in fact, starts from the main requirement analysis of the road electric vehicle which is considered as reference. Then, a wide range of parameters, related to the characteristics of propulsion system components and resistance forces, are evaluated to build a parametric model of the propulsion system running on a road. In this way, a procedure for the evaluation of vehicle performance is accomplished within the developed simulation environment. Therefore, the procedure allows all the requirements to be satisfied, under different operative conditions, through an iterative procedure of verification for the imposed parameters. The tested operative conditions are represented in this paper by standard driving cycles, expressed in terms of vehicle speed and autonomy requirement.

关键词： Systems engineering MBSE approach object-oriented modelling and simulation electric vehicles

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modelling and Control of Big Data Frameworks

Modelling and Control of Big Data Frameworks

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20th World Congress of the International-Federation-of-Automatic-Control (IFAC)

作者： Leva, Alberto Papadopoulos, Alessandro Vittorio Politecn Milan DEIB Milan Italy Malardalen Univ IDT Vasteras Sweden

We present a model library conceived to design and assess critical components of big data frameworks, with a control-centric approach. The library adopts the object-oriented paradigm, using the Modelica language. Continuous-time and algorithmic models can be mixed, allowing to represent control code with high fidelity, and to reduce the simulation effort to the minimum required. We discuss the used modelling principles, describe the library, and show some design examples. (C) 2017, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Big data Computing systems Control-oriented modelling object-oriented modelling and simulation

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object-oriented modelling of industrial PID controllers

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IFAC Proceedings Volumes 2012年第3期45卷 152-157页

作者： Alberto Leva Marco Bonvini Martina Maggio Politecnico di Milano Dipartimento di Elettronica e Informazione Piazza Leonardo Da Vinci 32 - 20133 Milano Italy PhD student at the Dipartimento di Elettronica e Informazione

This paper presents a library of (PID) controller models adopting the object-oriented approach, and written in Modelica. Peculiar to this work is that controllers are represented both as dynamic continuous-time and digital models, achieving consistence between the two and accounting for the functionalities of typical industrial implementations. This allows the designer to use realistic controllers, maintaining the possibility of choosing the continuous-time or digital (event based) representation. The former allows for example for variable-step simulation, to the advantage of efficiency, while the latter represents very realistically the actual control system's operation, clearly at the cost of more simulation time. Beside standard PI and PID controls, in this work also autotuning is (initially) considered, and some application examples are reported to show how the presented library can ease system studies involving (PID) controls.

关键词： object-oriented modelling and simulation PID control continuous-time control digital control

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