European Projects

  • Industry 4.0 is focused on information systems bringing together data from a large variety of sources. These data are subject to analytics to become the high fidelity information that enables systems to become more intelligent and autonomous. In these digital processes, Artificial Intelligence (AI) plays a central role in creating the necessary autonomy. In the Industrial transformation, there are frontrunners, followers and laggards among professionals, students and teachers. This AI-focused education project brings these groups together to accelerate the digital transformation. Next to teaching new generations of students, the professional education of technical workers and teachers is crucial because most of the current workforce has not received formal education in these digital technologies. This project will deliver state-of-the-art AI education using practical industry-relevant use cases to professionals and students in four countries, in co-operation with private companies.

    • REFERENCE CODE: 21050

    • FUNDING: European Institute of Innovation & Technology

    • PROGRAMME: EIT Manufacturing – EIT Manufacturing (KIC LE)

    • PERIOD OF EXECUTION: 01/01/2021 – 31/12/2021

    • COORDINATOR: Gil Manuel Magalhães de Andrade Gonçalves

    • WEBSITE: http://www.factoris.digital/

  • Innovative Solutions in Future Stations, Energy Metering and Power Supply (IN2STEMPO) addresses the call S2R-CFMIP3- 01-2017 Smart System Energy Management Solutions and Future Station Solutions. IN2STEMPO aligns with the Shift2Rail objectives and aims to reduce lifecycle costs, improve reliability and punctuality, whilst increasing capacity, enhancing interoperability, and improving the customer experience.
    The IN2STEMPO Smart Power Supply activities seek to contribute to the development of a railway smart grid based on the development of a unique railway power grid in an interconnected system. This new railway network will integrate smart metering, innovative power electronic components, energy management and energy storage systems. This new concept will lead to improved and optimized train traffic, energy costs, and energy supply security for the railway system. In parallel it will allow for optimized solutions to be developed through optimizing investment, operation costs and maintenance. The IN2STEMPO Smart Metering research activities will realize a non-intrusive smart metering sensor network at a railway system level. It will demonstrate an open system and interface for data collection, aggregation, and analysis at an open source ODM (Operational Data Management) level. The applications will exploit the energy analysis process with the aim of enhancing energy decision-making and line operation patterns. Other possible applications include preventative maintenance plans, asset management and Life Cycle Cost dashboards.

    • REFERENCE CODE: 777515

    • FUNDING: European Commission

    • PROGRAMME: H2020|SC|Transport – H2020|Societal Challenges|Transport

    • PERIOD OF EXECUTION: 01/09/2017 – 31/08/2022

    • COORDINATOR: António José de Pina Martins

    • WEBSITE: https://cordis.europa.eu/project/id/777515

  • Europe’s power system has seen significant changes in recent decades, notably the development of renewable energy sources. However, this transition is far from complete, and further changes are essential to make our energy system ready to play its part in realizing the climate goals set at COP21. At present, renewable energy sources are increasing their share of electricity generation. This is particularly the case for offshore wind energy. InnoDC’s 14 participants prepare 15 early career researchers to play their role in the energy transition that will take place over the next 20-40 years.
    The project focusses on the development of the electricity transmission system, targeting the connection of offshore wind, the integration of offshore wind with the existing power system (including the use of HVDC), and the operation of the future power system where large-scale wind is connected to a hybrid AC and DC power system. Technological development for offshore wind is ongoing. This research project focusses on the models and methodologies for the integration of these new technologies (e.g. offshore wind turbines, VSC HVDC converters, long AC cables) into the power system.
    Challenges in these areas will be addressed in this project: firstly, these new devices behave inherently differently to traditional power system components. Secondly, the multi-actor/intersectoral nature of these systems means that they have distinct elements and devices interfacing with each other, each with limited information of the overall system.
    The project will train the researchers in developing prototype tools to aid the developers and users of these new energy systems.

    • REFERENCE CODE: 765585

    • FUNDING: European Comission

    • PROGRAMME: H2020|ES|MSC – H2020|Excellence Science|Marie Curie

    • PERIOD OF EXECUTION: 01/09/2017 – 31/08/2021

    • COORDINATOR: Helder Filipe Duarte Leite

    • WEBSITE: https://innodc.org

National Projects

  • The REFARMING project is an integrated R&D initiative that brings together leading research institutions, including SYSTEC (FEUP), CMUP, GreenUPorto, ICT, and FCUP, to address some of the most pressing challenges in modern agriculture. The project focuses on developing sustainable and innovative solutions to promote resilience to climate change and improve the nutritional quality of horticultural crops.

    With a strong emphasis on controlled production systems, such as advanced technological greenhouses and vertical farming, REFARMING integrates cutting-edge technologies and energy optimization strategies to create efficient, sustainable, and scalable agricultural practices. By leveraging multidisciplinary expertise in biology, agricultural processes, mathematical modeling, control systems, and automation, the project aims to redefine the future of food production.

    Project Website: https://systec.fe.up.pt/project-refarming

  • This project focus on manufacturing flexibility and sustainability. The former is researched by optimizing scheduling operations in flexible manufacturing systems through the cumulative integration of the several sub-problems faced in manufacturing flexible systems.
    Sustainability is promoted via optimizing resource consumption and pollutant emissions along with the usual efficiency measures (makes pan, tardiness, workload, etc.) for production operations scheduling problems. Regarding the emissions, it also accounts for the possibility of buying and/or selling pollution permits. This project aims at developing mathematical programming models as well solutions methods to solve them for the problems. In addition, and due to the NP-hardness nature of the problems under consideration, we also aim at proposing solution approaches based on evolutionary algorithms that are capable of finding good solutions in a reasonable are also proposed.

    • REFERENCE CODE: POCI-01-0145-FEDER-031821

    • FUNDING: FCT – Fundação para a Ciência e a Tecnologia

    • PROGRAMME: FCT-UID – Programas Integrados de IC&DT (2015 – 2020)

    • PERIOD OF EXECUTION: 01/07/2018 – 30/06/2021

    • COORDINATOR: Dalila Benedita Machado Martins Fontes

    • WEBSITE: https://www.inesctec.pt/pt/projetos/fast-manufacturing

  • The aim is the development, analysis, and demonstration in case studies of controller design for networked CPS based on optimal control (OC). The task on dynamic programming-based OC problems derives Hamilton-Jacobi type conditions for systems with fast and slow dynamics, and sampled control systems. The task on algorithms on distributed OC combines approximated solutions of the necessary conditions of optimality with methods of distributed optimization. The task on distributed model based predictive control (MPC) for networked CPS uses theoretical tools from MPC for networked CPS. It addresses distributed MPC for coordinated output regulation in multiagent systems, and cloud based MPC of networked CPS. Finally, there are two applied tasks: energy management with multiple renewable sources, and multiple vehicle control and coordination.

    • REFERENCE CODE: NORTE-01-0145-FEDER-031411

    • FUNDING: FCT – Fundação para a Ciência e Tecnologia

    • PROGRAMME: P2020|COMPETE – Projetos em Todos os Domínios Científicos

    • PERIOD OF EXECUTION: 15/08/2018 – 14/08/2021

    • COORDINATOR: Fernando Manuel Ferreira Lobo Pereira

    • WEBSITE: http://ramses.inesc.pt/HARMONY

  • IMPROVE aims to develop theoretical tools and algorithms in the field of mobile robotic systems using an approach that directly integrates not only the main task but also other objectives (economic, performance, robustness, security) in the presence of constraints and complex unstructured scenarios. Emphasis will be placed on developing non-linear control and optimization methods that are by construction formally correct, including fault detection and isolation strategies, for the purpose to obtain high-performance robotic systems that meet the requirements of end-users. For research to be oriented in high impact areas, the IMPROVE project will focus on the following classes of applications: Logistics and handling in industry using mobile robots; Cooperation of autonomous air and marine robotic vehicles for ocean monitoring and sampling.