This talk will present the stakes of flow management in the health domain, as well as the specificities of healthcare production systems compared to manufacturing systems.
We will see some examples of work, carried out in the G-SCOP laboratory, showing the contribution of engineering sciences, and more particularly of industrial engineering, for the study and the improvement of the organization of various healthcare production systems. This talk will thus show how modeling, performance evaluation, mathematical optimization, and risk analysis can contribute to making the management of healthcare production systems more efficient.
Maria Di Mascolo
French National Center for Scientific Research
Maria Di Mascolo, is Senior Researcher at the CNRS (French National Center for Scientific Research), and a member of the G-SCOP (Grenoble-Sciences for Design, Optimization and Production) laboratory. Her main scientific interests are related to the modelling, analysis and optimization of systems for the production of goods and services, and in particular healthcare production systems.
Her objective is to develop methods and tools to assist in making decisions that guarantee a good performance to production systems, despite uncertainties. The decisions to be made concern the design of production systems (including the control or maintenance policies to be implemented), as well as the planning of activities to be carried out, or the management of flows, with a special interest in the sustainability and human aspects.
She co-leads the GISEH (Hospital Systems Management and Engineering) technical committee of the SAGIP (French Society of Automatic Control, Industrial and Systems Engineering), and is editor-in-chief of the ISTE OpenScience journal “Industrial and Systems Engineering“. She is Deputy Head of Sustainable Industrial Engineering Master’s degree at Grenoble Institute of Technology.
During the last two decades, power electronic converters have become key enabling technology in very important areas, such as renewable energy and distributed generation, smart grids, transportation, industry, consumer electronics etc.
Power electronics converters are required to fullfil many demanding tasks, but all of them share some basic requirements, including the optimization of energy conversion, high flexibility and low cost, according to the concept of life cycle assessment (LCA). Multilevel Converters (MLC), early proposed for high power, high voltage applications, are gaining popularity and applications at all power levels demonstrating unusual flexibility even at low power. One key point in multilevel converters, is their ability to reduce the harmonic content affecting their input/output currents and voltages.
Their modulation patterns are very often imposed by algorithms consisting of preliminary off-line computations and subsequent real-time application of the precalculated patterns through look up tables. These approaches need large amount of memory space, can reduce precision of commutation angles and are not very flexible in closed loop operations. Analytical methods, instead, offer significant advances: exact problem formulation, easy and effective real-time implementation, capability of selective harmonic elimination or mitigation, possibility to cascade the modulator with the outer control loops. During the speech, after an introduction, some analitycal methods for modulation of MLC will be introduced and discusse in detail, hence, some examples of practical implementation will be reported.
Prof. Carlo Cecati
University of L’Aquila, Italy
Carlo Cecati (Fellow, IEEE) (M’90-SM’03’-F’06) received the Dr. Ing. Degree in Electrotechnical Engineering from the University of L’Aquila, L’Aquila, in 1983. Since then, he has been with the same university where he is a Professor of Industrial Electronics and Drives since 2006. From 2015 to 2017, he has been a Qianren Talents Professor with the Harbin Institute of Technology, Harbin, China.
His primarily research interests include power electronics, distributed generation, e-transportation and smart grids. Prof. Cecati has been Co-Editor-in-Chief (2010-2012) and Editor-in-Chief (2013-2015) of the IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS. He has been a corecipient of the 2012 and the 2013 Best Paper Award from the IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, of the 2012 Best Paper Award from the IEEE INDUSTRIAL ELECTRONICS MAGAZINE and of the 2019 Outstanding Paper Award from the IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS.
In 2017 he received the Antony J. Hornfeck Award from the IEEE Industrial Electronics Society, in 2019 received the title of “Commander of the Republic of Italy” from the President of the Republic of Italy, in 2021 he received the Eugene Mittlemann Achievement Award from the IEEE. He is Chief Technical Officer at DigiPower Ltd., a R&D company active in the field of power electronics.
Set-valued sliding-mode control and differentiation, usually suffer from the well-known chattering phenomenon, which deteriorates their performance and can even sometimes prevent their use. It is known that one important source of chattering (at both the output and the input, which takes a bang-bang-like shape) is an inappropriate discretization, which yields the so-called digital, or numerical chattering.
The explicit Euler discretization, which is widely employed, is known to be the source of numerical chattering (see the works of Galias et al). Recently it has been shown that the implicit Euler discretization yields very efficient algorithms to suppress the numerical chattering, while keeping all the nice and powerful properties of the continuous-time counterparts: rigorous definition of a discrete sliding surface, finite-time convergence, robustness to matched (and some unmatched) disturbances, Lyapunov stability, insensitivity to the control gain during the sliding-motion. Several experimental results have validated the theoretical findings. In this talk we will introduce the implicit Euler method on several kinds of systems (linear, Lagrange mechanical, with matched or unmatched disturbances) and several kinds of SMC controllers (first-order, twisting, super-twisting, high-order) as well as differentiators. Most importantly it will be shown the deep link between the implicit discretization and maximal monotone operators, the Yosida approximations of Convex Analysis and the so-called proximal algorithms, which shows that the implicit discretization is not an implementation trick, but a discretization method.
Bernard Brogliato
Inria Grenoble-Rhône-Alpes Research Centre
Bernard Brogliato was born in Saint- Symphorien-de-Lay, France, in 1963. He received the Agrégation de mécanique from the Ecole Normale Supérieure de Cachan, Cachan, France, in 1986, and the Ph.D. and Habilitation à Diriger des Recherches degrees in automatic control from Grenoble INP, Grenoble, France, in 1991 and 1995, respectively. From 1991 to 2001, he was with Centre national de la recherche scientifique, Grenoble, France. Since 2001, he has been with Inria Grenoble Rhône-Alpes, Montbonnot-Saint-Martin, France. His main research interests include nonsmooth dynamical systems analysis, control and modeling, and dissipative dynamical systems.
The development of inexpensive and fast computers, coupled with the discovery of efficient algorithms for dealing with polynomial equations, gave rise to some exciting new applications of algebraic geometry and commutative algebra. One of the main goals of this talk is to show how some tools borrowed from these two fields can be efficiently employed to solve relevant control problem.
After a brief introduction to some algebraic objects and techniques, it is shown how such tools and methodologies can be applied to a wide variety of topics concerning control theory and its application, such as the design of observers for nonlinear plants, the motion planning of mobile robots, the inverse kinematics of robot manipulators, the characterization of invariant sets for nonlinear systems, and the decomposition of a polynomial in sum of squares.
Corrado Possieri
Department of Civil Engineering and Computer Engineering
of the University of Rome “Tor Vergata”, Rome – Italy
Corrado Possieri received the bachelor’s and master’s degrees in medical engineering from Università di Roma “Tor Vergata” in 2011 and 2013, respectively. He received the Ph.D. degree in Computer Science, Control, and Geoinformation from Università di Roma “Tor Vergata” in 2016. During his Ph.D., he visited the University of California, Santa Barbara as a Research Scholar. In 2018, he joined the Dipartimento di Elettronica e Telecomunicazioni of the Politecnico di Torino where he was an Assistant Professor. In 2019, he joined the Istituto di Analisi dei Sistemi ed Informatica “A. Ruberti” of the National Research Council of Italy, where he was a Researcher. In 2022, he joined the Dipartimento di Ingegneria Civile e Ingegneria Informatica of the Universita` di Roma “Tor Vergata”, where he is currently an Assistant Professor.
He is the author of more than 110 scientific papers published in peer reviewed journals and conference proceedings, of a book, and of an international patent. He served as Vice-Chair on Social Media of the Technical Committee on Control Design of the International Federation of Automatic Control, as a member of the organizing committee of several international conferences, and as Associate Editor for PLoS One.
His research interests include the design of reinforcement learning algorithm, the application of symbolic computation to control theory, and the design of observers for nonlinear systems.
Differential games have been studied for decades and have played, and continue to play, an important role in control engineering and decision processes. In this talk some basics on differential games, their relation to optimal control and their relevance to “classical” control engineering problems are briefly recalled. Then, starting with linear quadratic differential games, some of the “peculiarities” of differential games (or dynamic games, as they are referred to in the discrete-time setting) are discussed and various strategies to obtain their solution – via model-based or data-driven algorithms – are presented.
Turning then to a more general class of nonlinear differential games, strategies to obtain their solutions (or approximations thereof) are discussed. Various case studies are considered, with a particular emphasis on applications to robotic systems including, for instance, the multi-agent collision avoidance problem. Finally, the relevance of differential games to current challenges in distributed control are briefly discussed.
Thulasi Mylvaganam
Faculty of Engineering, Department of Aeronautics,
Imperial College, London – United Kingdom
Thulasi Mylvaganam was born in Bergen, Norway, in 1988. She received the M.Eng. degree in Electrical and Electronic Engineering and the Ph.D. degree in nonlinear control and differential games from the Department of Electrical and Electronic Engineering, Imperial College London, U.K., in 2010 and 2014, respectively. From 2014 to 2016, she was a Research Associate in the same department. From 2016 to 2017, she was a Research Fellow with the Department of Aeronautics, Imperial College London, UK, where she is currently a Senior Lecturer (Associate Professor). Her research interests include nonlinear control, dynamic optimisation, distributed control and data-driven control. While her research is mainly focused about fundamental aspects of control engineering, since joining the Department of Aeronautics, she has gained a special interest in its applications to robotics. She a Senior Member of the IEEE, a Member of the IEEE CSS Conference Editorial Board, of the EUCA Conference Editorial Board and a Member of the IFAC Technical Committee 2.4 (Design Methods – Optimal Control). She has served as Associate Editor for several conferences, including the IEEE Conference on Decision and Control, the IFAC World Congress, the American Control Conference, the European Control Conference and the IFAC Workshop on Control Applications of Optimization. She was Financial Chair for the 2022 European Control Conference.
Copyright © ICCAD 2023
