ERC Consolidator Grant C-NORA: Micro-Macro Secure Control of Infinite-Dimensional Transport Systems In various real-world systems, continuous (in time/space) transport is the main dynamic characteristic. Two examples are blood transport and epidemics transport. Motivated by the urgent need of design of efficient/safe, epidemics spreading suppression and blood transport monitoring strategies, C-NORA suggests to view different, heterogeneous systems from a “transport” perspective, aiming at development of designs that harmonize control at both micro and macro levels, while addressing key technical features. Focusing on the transport phenomenon provides an opportunity to develop computationally tractable control designs for large-scale, distributed parameter transport systems and enables combination of Partial Differential Equation (PDE) control tools with traffic flow control tools, towards control and estimation of general systems. More information inhttps://c-nora.tuc.gr/ ITN CONFLEX: Control of flexible structures and fluid-structure interactions The ConFlex consortium aims to train the next generation of researchers on the control of flexible structures and fluid-structure interactions, using and also contributing to the latest advances in control theory and energy-based modelling. The ConFlex consortium comprises a group of 15 academics with expertise in control theory, complex dynamical systems (in particular, distributed parameter systems (DPS)), fluid dynamics, aeroelasticity, power electronics, swimming theory and marine engineering, working in either mathematics or engineering departments, with a strong history of internal collaboration. ConFlex academics are located at 10 beneficiary nodes in the United Kingdom, France, The Netherlands, Spain, Germany and Israel. The ConFlex consortium also has four academic partners (located in USA, China, Canada and France) and 11 prestigious industrial partners. https://www.conflex.org/ Beneficiaries Tel Aviv University (Tel Aviv) University of Warwick (Warwick) Imperial College London (Imperial) Universiteit Twente (Twente) Bergische Univer-sität Wuppertal (Wuppertal) Université de Franche-Comté (Besancon) Université de Bordeaux (Bordeaux) University of Exeter (Exeter) Universidad Autónoma de Madrid (Madrid) Non-Beneficiary Partners Airbus Operations GmbH ( Airbus) ASML ( ASML) BAE Systems Surface Ships Ltd (BAE) CENER(CENER) DLR - German Aerospace Centre (DLR) FTI Consulting (FTI) Offshore Renewable Energy Catapult (OREC) ONERA (ONERA) Rafael Advanced Defence Systems (Rafael) Thales Alenia Space (Thales) XEMC Wind-power (XEMC) Chinese Academy of Sciences (Beijing) Illinois Institute of Technology (Chicago) University Claude Bernard in Lyon (Lyon) University of Waterloo (Waterloo) (ERC) Advanced GraNT "DYCON - DYNAMIC CONTROL" DyCon project aims at making a breakthrough contribution in the broad area of Control of Partial Differential Equations (PDE) and their numerical approximation methods by addressing key unsolved issues appearing systematically in real-life applications. To this end, we pursue three objectives: To contribute with new key theoretical methods and results To develop the corresponding numerical tools, and To build up new computational software, the DYCON-COMP computational platform, thereby bridging the gap to applications. The field of PDEs, together with numerical approximation and simulation methods and control theory, has evolved significantly in the last decades in a cross-fertilization process, to address the challenging demands of industrial and cross-disciplinary applications such as, for instance, the management of natural resources, meteorology, aeronautics, oil industry, biomedicine, human and animal collective behavior, etc. Despite these efforts, some of the key issues still remain unsolved, either because of a lack of analytical understanding, of the absence of efficient numerical solvers, or of a combination of both. This project identifies and focuses on six key topics that play a central role in most of the processes arising in applications, but which are still poorly understood: Control of parameter-dependent problems Long time horizon control Control under constraints Inverse design of time-irreversible models Memory and hybrid PDE/ODE models Finite versus infinite-dimensional dynamical systems These topics cannot be handled by superposing the state of the art in the various disciplines, due to the unexpected interactive phenomena that may emerge, for instance, in the fine numerical approximation of control problems. The coordinated and focused effort that we aim at developing is timely and much needed in order to solve these issues and bridge the gap from modeling to control, computer simulations and applications. http://cmc.deusto.eus/dycon/
