Rui Araújo – ProjectsPrincipal Investigator in R&D Projects:21. SOMIPs - Simulation, Optimization and Monitoring Using AI-Based Digital Twin Technology for Incineration Plants Abstract: The operation of Biomass Valorization Plants (CVB) is complex due to the great variability of factors related to biomass, such as humidity, types and granulometry, as well as due to the condition of the equipment, quantity of pollutants produced, etc. The uncertainty regarding operational factors implies a high need for human intervention in balancing the various process parameters. This model of constant human supervision of industrial processes, transversal to different production sectors, places the operator with a preponderant role in the performance and efficiency of the processes, with invariably large associated inefficiencies. 20. RELIABLE - Advances in Control Design Methodologies for Safety Critical Systems Applied to Robotics Reference number: PTDC/EEI-AUT/3522/2020; Host institutions: Institute of Systems and Robotics - University of Coimbra (ISR-UC); Faculty of Engineering of the University of Porto (FEUP) (leader partner); Center of Systems and Technologies - University of Porto (SYSTEC-UP); Start date: 2021/02/01; End date: 2024/01/31; Financing: Foundation for Science and Technology (FCT); Note: principal investigator at ISR-UC. Abstract: Advanced robotics, smart sensors, and related control systems methodologies have the potential to be disruptive technologies that may generate significant societal benefits, but it may also produce serious consequences in case of failure, particularly in safety-critical applications. Safety is a critical requirement for a wide range of engineering systems, and engineering design of such systems is complex and involves many technical fields ranging from conceptual algorithmic level design with formal guaranties to hardware and software development, implementation, and operation. This project is mainly devoted to conceptual aspects, but to illustrate, demonstrate and also assure that it is driven by high-impact safety-critical application systems, RELIABLE will also focus on the following case studies: This proposal brings together experts from the areas mentioned above involving a team of PhD students, pos-docs and several faculty members with the University of Porto and University of Coimbra. The merit of this research program is that it targets fundamental/conceptual research, but it is also well motivated by applications. The theoretical solutions envisioned will be strongly rooted in research work done by the team, where obtaining formal guarantees of safety, robustness, stability and performance is a key objective. At practical level, one key objective is to demonstrate and integrate some of the algorithms developed in software tools for command and control of single and multiple robotic systems, simulate and test within hardware in the loop, and validate through real field tests. 19. SmartWater - Smart Water Meter and Intelligent Water Analytics Platform for Water Pipeline Leakages Localization and End-Use Water Demand Outline Reference number: SmartWater/2019/47730; Host institutions: Institute of Systems and Robotics - University of Coimbra (ISR-UC); ‘‘CWJ - Projecto, SA’’ (CWJ-P, leader partner); ‘‘CWJ - Componentes, SA’’ (CWJ-C); ‘‘UtilityARTS, SA’’ (UARTS); Start date: 2020/09/01; End date: 2023/06/30; Financing: co-financing by “Portugal 2020” (PT2020), in the framework of the “Centro Region Operational Programme” (CENTRO 2020), and by the European Union through the European Regional Development Fund (ERDF); Note: principal investigator at ISR-UC. Abstract: CWJ group of companies (CWJ Group) has already developed an Automated Metering Infrastructure (AMI) for Water Distribution Networks (WDN) supported in Wireless Water Meter Transceivers (WWMT), capable of being installed in the existing standard water meters, that can establish a meshed Wireless Sensor Network (WSN) among them. This WSN is created through the Low Power Wide Area Network (LPWAN) - All for Everyone - Energy Aware (AfE-EA) communications protocol, developed by CWJ-P. The AfE-EA protocol uses a mesh topology that can provide the total coverage of all the water infrastructure’s devices, including devices placed in building’s basements, normally not covered by other IoT communications protocols. Since this business concept in now completely established on the market by CWJ Group, with rollouts in several WDN infrastructures in Portugal, following the particular innovation that the market is demanding, this project aims to obtain an Integrated Management of Efficiency System (IMES) that includes a Smart Water Meter (SWM) with innovative functionalities and an Intelligent Water Analytics Platform (IWAP). 18. EVAI Charge - Artificial Intelligence Electric Vehicle Charge for Low Carbon Buildings Reference number: EVAI/2019/47196; Host institutions: Institute of Systems and Robotics - University of Coimbra (ISR-UC); ‘‘VPS - Virtual Power Solutions, Lda’’ (leader partner); Start date: 2021/01/01; End date: 2023/06/30; Financing: co-financing by “Portugal 2020” (PT2020), in the framework of the “Centro Region Operational Programme” (CENTRO 2020), and by the European Union through the European Regional Development Fund (ERDF); Note: principal investigator for the computational intelligence part at ISR-UC. Abstract: The European Union has been increasingly interested and concerned with energy policy in general. In the Clean Energy Package (2015 and 2019), citizens are at the centre of concerns and the need to be able to take advantage of new technologies to reduce energy bills and participate actively in the market is highlighted. One of the priorities is to “facilitate the participation of consumers (…) through smart grids …”. The Green Deal, released in December 2019, sets out an approach for a deep transformation of the EU economy to a new growth strategy based on clean energy supply across all sectors, requiring the deployment of innovative technologies and infrastructure, such as smart grids. 17. SYNAPPS - Platform for Estimation, Control, and Optimization of Waste Water Treatment Plants Reference number: CENTRO-01-0247-FEDER-046978; Host institutions: Institute of Systems and Robotics - University of Coimbra (ISR-UC); ‘‘Itecons - Instituto de Investigação e Desenvolvimento Tecnológico para a Construção, Energia, Ambiente e Sustentabilidade’’; ‘‘CTGA - Centro tecnológico de Gestão Ambiental, Lda’’ (leader partner); Start date: 2021/01/01; End date: 2023/06/30; Financing: co-financing by “Portugal 2020” (PT2020), in the framework of the “Centro Region Operational Programme” (CENTRO 2020), and by the European Union through the European Regional Development Fund (ERDF); Note: principal investigator for the computational intelligence part at ISR-UC. Abstract: Wastewater generated by the vast world population is an important source of pollution. Such wastewater can also accelerate the loss of biodiversity and prevent the achievement of objectives set by the international community regarding the good state of the waters. As far as the European Union is concerned, legislative acts have clear and binding objectives for member states. However, it is completely flexible regarding the means to achieve these objectives, allowing for alternative solutions and encouraging innovation in wastewater treatment strategies. 16. InGestAlgae - Intelligent Platform for Microalgae Production Management Reference number: CENTRO-01-0247-FEDER-046983; Host institutions: University of Coimbra (UC); OnControl Technologies, Lda (leader partner); Partner institution: BuggyPower (Portugal) - Management and Production of Biomass, Lda; Start date: 2021/01/18; End date: 2023/06/30; Financing: co-financing by “Portugal 2020” (PT2020), in the framework of the “Centro Region Operational Programme” (CENTRO 2020), and by the European Union through the European Regional Development Fund (ERDF); Note: co-principal investigator at UC. Abstract: This project aims to develop an integrated management system, supported by computational intelligence systems, to support the microalgae production process. This system, called IngestAlgae, will consist of several modules, present in the different layers of industrial automation: shop floor, control, supervision and management. 15. iProMo - Intelligent System for Control of Milling Processes Reference number: CENTRO-01-0247-FEDER-069730; Host institutions: University of Coimbra (UC); OnControl Technologies, Lda (leader partner); Partner institution: Cimpor - Cements of Portugal; Start date: 2021/02/01; End date: 2023/06/30; Financing: co-financing by “Portugal 2020” (PT2020), in the framework of the “Centro Region Operational Programme” (CENTRO 2020), and by the European Union through the European Regional Development Fund (ERDF); Note: co-principal investigator at UC. Abstract: This project aims to investigate and develop an intelligent system for horizontal mills, in order to increase the efficiency of the grinding process and minimize downtime due to breakdowns. The optimization will be achieved by estimating, in real time, operational parameters critical to the process, which cannot be directly measured, due to the lack of sensors for this purpose. These parameters are, the level of filling of the mill, the impact zone of the grinding bodies, the setting of the cement and the fineness of the particles; these last two are parameters related to the quality of the milling. In addition to the estimation of critical parameters, it is also the objective of this project to develop tools to assist in the maintenance and detection of anomalies in sensors. The systems developed here, will be created based on the operational data of the process together with other parameters external to the mill, from vibration sensors, to be installed in the base and in the grinding cylinder, voltage and current signals of motors, others process signals (air flows, scale weights, etc.), in conjunction with mathematical modeling, signal processing and computational intelligence techniques. The acquisition of external data will take place through modular and expandable hardware modules (to be developed during the course of this project), composed of a data acquisition, processing and management system in an “edge analytics” concept. This solution complements the portfolio of advanced control solutions for horizontal rotary mills, made available by Oncontrol. 14. SIICEI - Intelligent System for Identification of Electrical Loads in Industrial Equipment Reference number: SIICEI/2017/33338; Host institutions: University of Coimbra (UC); OnControl Technologies, Lda (leader partner); Advanced Home, Lda; Start date: 2018/11/01; End date: 2021/07/31; Financing: co-financing by “Portugal 2020” (PT2020), in the framework of the “Centro Region Operational Programme” (CENTRO 2020), and by the European Union through the European Regional Development Fund (ERDF); Note: principal investigator at UC. Abstract: The SIICEI project has the main goal of research and development of an electrical loads separation and identification system for industrial applications, and subsequent processing, for energy consumption and operation monitoring. The system to be developed shall allow the energy consumption profile identification of each electrically-powered equipment (charge), in real-time, using computational intelligence and signal processing methodologies, and using only the electrical energy signals only at the industrial installations energy input. So, with a reduced investment and quick installation it is possible to identify the energy consumption, measure equipment operation periods, and also, drive new applications of the gathered data. 13. CONNECTA-X - Interoperable System and Modules for Appliance Integration in Intelligent Home Ecosystems Reference number: CONNECTA-X/2017/33354; Host institutions: University of Coimbra (UC); Critical Software, SA (leader partner); Start date: 2018/10/01; End date: 2021/09/29; Financing: co-financing by “Portugal 2020” (PT2020), in the framework of the “Competitiveness and Internationalization Operational Programme” (COMPETE 2020), and by the European Union through the European Regional Development Fund (ERDF); Note: principal investigator at UC. Abstract: The CONNECTA-X project performed R&D on interoperable system and modules for integration of appliances in intelligent homes; including R&D on themonitoring integration of “Internet of Things” (IoT) and Smart Meters and aims to develop a structure for the embedded market, a platform for communication, gathering, and treatment of data in the computational intelligence and monitoring device monitoring domains, that should support the development of new added-value products and services on the IoT and Smart Meters domain. 12. IMPROVE - Nonlinear Control, Estimation and Fault-Detection Tools with Provably Guarantees for Mobile Robotic Systems Reference number: POCI-01-0145-FEDER-031823; Host institutions: Institute of Systems and Robotics - University of Coimbra (ISR-UC); Faculty of Engineering of the University of Porto (FEUP) (leader partner); Institute of Systems and Robotics - University of Porto (ISR-UP); Start date: 2018/06/01; End date: 2022/01/31; Financing: co-financing by the Foundation for Science and Technology (FCT), the “Competitiveness and Internationalization Operational Programme” (COMPETE 2020), Portugal 2020 (PT2020), and the European Union through the European Regional Development Fund (ERDF); Note: principal investigator at ISR-UC. Abstract: The aim of this project is to develop system theoretical tools and algorithms in framework of mobile robotic systems that explicitly integrate in the conceptual formulation not only the desired main task but also other key objectives (e.g., economic, performance, robustness, safety, system observability properties, communication behavior and interaction with other systems, etc.) in the presence of challenging restrictions and unstructured environments. The emphasis will be placed on the design of nonlinear and optimization based control and estimation procedures that are provably accurate by construction for single and multiple robotic systems including fault-detection and isolation strategies in order to obtain high performance robotic systems capable of meeting the end-user requirements. 11. TOOLING4G - Advanced Tools for Smart Manufacturing Reference number: TOOLING4G/2016/24516; Host institutions: University of Coimbra (UC); CENTIMFE - Technological Center for Moulds, Special Tools and Plastics (overall management); Aníbal H. Abrantes - Industries of Moulds and Plastics, S.A. (leader); the project is a partnership among 30 entities, including 20 companies, and 10 non-corporate R&D institutions, higher education entities, and technological interface centers; Start date: 2018/03/01; End date: 2022/10/31; Financing: co-financing by the “Competitiveness and Internationalization Operational Programme” (COMPETE 2020), Lisbon Regional Operational Program 2014/2020 (LISBOA2020), Portugal 2020 (PT2020), and by the European Union through the European Regional Development Fund (ERDF); Note: principal investigator for the PPS2 part at the UC. Abstract: The TOOLING4G project aims to make an important contribution to the moulds and plastics industry, enabling the partner companies to create the conditions to become competitive and to overcome global market challenges, by creating internally conditions for production flexibility.
The project is structured in 7 large PPSs (Product, Process or Service), including hybrid manufacturing processes; intelligent tools/systems; efficient tools for multi-material products’ manufacturing; multi-process tools; industry digitalization; sustainable “zero defect” production chain; management and dissemination.
The consortium consists of 21 mould-making and plastics companies and 10 entities of the research and innovation system, including higher education institutions and technology interface centres, that possess a set of complementary skills and human capital resources.
Several innovations are expected to be developed in the project, mainly centred in materials, products and processes, and also in the endogenization of technologies and organizational paradigms in the context of the Industry 4.0 concept. 10. SMITEn - Smart Meter Integrated Test Environment Reference number: SMITEn/2016/023613; Host institutions: Institute of Systems and Robotics - University of Coimbra (ISR-UC); Critical Software, SA; Start date: 2017/10/01; End date: 2019/09/30; Financing: co-financing by the “Competitiveness and Internationalization Operational Programme” (COMPETE 2020), Portugal 2020 (PT2020), and by the European Union through the European Regional Development Fund (ERDF); Note: principal investigator at ISR-UC. Abstract: Smart-Grids are an integrated vision for the future of energy supply networks in response to the current challenges of environmental sustainability, reliability and quality of the European energy supply. These infrastructures integrate various heterogeneous elements that should be well interconnected and whose interoperability will become increasingly complex and critical for the security and world economy. 9. KhronoSim - System for Simulation and Test of Complex Systems Reference number: KhronoSim/2016/17611; Host institutions: University of Coimbra (UC); Critical Software, SA (leader partner); Institute of Engineering of Porto; Start date: 2016/10/01; End date: 2018/09/30; Financing: co-financing by “Portugal 2020” (PT2020), in the framework of the “Competitiveness and Internationalization Operational Programme” (COMPETE 2020), and by the European Union through the European Regional Development Fund (ERDF); Note: principal investigator at UC. Abstract: Concepts such as “Fourth Industrial Revolution (Industry 4.0)” and “Internet of the Things (IoT)” boasted into the technology speech like a blizzard, touching those who use and interest themselves of technology almost as much as those developing it. Such concepts are not surprisingly more used than understood; more are those using the concepts than those actually understanding their implications. Surprisingly enough, the increase of use of technology by the population at large, makes that security is not the least well-known aspect, though still not fully grasped however. 8. SCIAD - Self-Learning Industrial Control Systems Through Process Data Reference number: SCIAD/2011/21531; Host institutions: University of Coimbra (UC), and Acontrol; Start date: 2012/01/01; End date: 2014/12/31; Financing: co-financing by QREN, in the framework of the “Mais Centro - Regional Operational Program of the Centro”, and by the European Union through the European Regional Development Fund (ERDF); Note: principal investigator at UC. Abstract: The objectives and scope of the project are in R&D on data-based control methodologies based auto-tuning and auto-adaptive approaches for PID and other controlers for linear and non-linear systems; R&D control methodologies based on process data for auto-design and auto-adaptation of controllers for linear and nonlinear systems; R&D on nonlinear control systems applying methods based on neural networks using processa data, and other methods; R&D on linear and non-linear multi-variable control methodologies; R&D of model predictive control (MPC) methodologies, considering knowledge driven and data driven approaches; R&D of MPC methods that are able to auto-tune, auto-adjust, auto-adapt, and learn the system model from observation of system variables; Research on the identification of process models by cognitive algorithms (neural networks, support vector regression (SVR), fuzzy systems, etc); Research of mathematical prediction methods and/for application on the optimisation of the MPC methods; R&D of mathematical optimisation, stability, and robustness of the researched control methodologies; R&D of learning methodologies for the determination of linguistic values of linguistic fuzzy variables, as well as for the determination of the control rules: R&D on evolutionary algorithms and/or genetic algorithms and/or hybrid and/or optimization methodologies and/or unsupervised learning methodologies for learning the linguistic variables and the rules for the knowledge base of a fuzzy controller; R&D on application to simulated processes, real prototype processes, and real industrial processes. 7. FAir-Control - Factory Air Pollution Control Reference number: E!6498; Host institutions: University of Coimbra (UC), and Acontrol; Start date: 2011/11/01; End date: 2013/10/31; Financing: Eurostars Programme of the EUREKA network, financed by “Fundação para a Ciência e a Tecnologia” (FCT), of the Ministry of Education and Science, “Agência de Inovação” (AdI), and the Seventh Framework Programme for Research and Technological Development (FP7) of the European Union; Note: principal investigator at UC. Abstract: The aim of this project is to develop advanced real-time control methodologies for cost optimization of air pollutants mitigation systems. The goal is the automatic control and optimization of the feed rates of mitigation chemicals introduced into the production process (Selective Non-Catalytic Reduction), in order to control the pollutants output on the stack within the legal limits, i.e. always taking in consideration the non-violation of regulations. 6. SInCACI - Intelligent Systems for Industrial Control, Acquisition and Communication Reference number: SInCACI/3120/2009; Host institutions: University of Coimbra (UC), and Acontrol; Start date: 2009/04/01; End date: 2012/03/31; Financing: “Mais Centro Operacional Program”, financed by “European Regional Development Fund” (ERDF), and “Agência de Inovação” (AdI); Note: principal investigator at UC. Abstract: The objectives and scope of the project are performing R&D on intelligent control and decision methods; Development of a general-purpose Fuzzy Control System (FCS); On-line process control and monitoring; Controller specification and implementation; Visualization of the process state; Devices/process failure reports; Direct application to industry problems; Research computational intelligence techniques for the development of soft sensors for industrial application; R&D on industrial communication and processing modules: industrial distributed real-time communication fieldbus protocols: ControlNet, Ethernet/IP, DeviceNet; ProfiNet. Relevant properties to industrial fieldbuses: Real-time operation, Reliability, Deterministic, Error-proof, Easy to extend and maintain. Direct application to industry problems; Selling on market. 5. FUZCTR - Development of Fuzzy Controllers for Modules of Manufacturing Systems Reference number: ACONTROL/ISR/001/2007; Host institution: “Institute of Systems and Robotics - University of Coimbra” (ISR-UC); Start date: 2007/08/27; End date: 2009/08/31; Financing: “AControl - Automação e Controle Industrial, Lda” company. Abstract: In this project the goal is to study and implement a fuzzy control system for industrial process control applications. The first applications will be in a cement kiln plant, including, as a first step, the control of the raw mill process. 4. STRNET - Development of Hardware/Software for Industrial Distributed Real-Time Systems Using the ControlNet Protocol Reference number: ACONTROL/ISR/002/2007; Host institution: “Institute of Systems and Robotics - University of Coimbra” (ISR-UC); Start date: 2007/08/27; End date: 2009/08/31; Financing: “AControl - Automação e Controle Industrial, Lda” company. Abstract: In this project the goal is to study and develop hardware and software of real-time system containint digital processing (microcontrollers) having the capacity of performing network communication with other modules using the ControlNet protocol, as well as the capacity of performing relevant processings in industrial automation and control environments. 3. Project of Creation of the Research & Development Division of Acontrol Reference number: CENTRO-07-0202-FEDER-002502; Host institution: University of Coimbra (UC); Principal contractor: Acontrol; Start date: 2008/09/01; End date: 2011/08/31; Financing: “IAPMEI - Instituto de Apoio às Pequenas e Médias Empresas e à Inovação” and “AControl - Automação e Controle, Lda”. Financed within ‘‘Projectos de Criação e Reforço de Competências Internas de I&DT’’ of ‘‘Sistema de Incentivos à Investigação e Desenvolvimento Tecnológico nas Empresas’’ (SI I&DT) of ‘‘Quadro de Referência Estratégico Nacional Portugal 2007-2013’’ (QREN); Note: principal investigator at UC. Abstract: The University of Coimbra participates as a specialized consultant in the area of intelligent systems and algorithms. 2. Computational Intelligence for System Monitoring, Diagnosis, and Control in Industrial Applications Reference number: SFRH/BDE/33295/2008, PhD fellowship in company entitled “System for Monitoring and Diagnosis Using Soft Sensors in Industrial Applications”; Host institutions: University of Coimbra (UC) and ISA; Start date: 2008/10/01; End date: 2012/09/30; Financing: Fundação para a Ciência e a Tecnologia (FCT), and “ISA - Instrumentação e Sistemas de Automação, Lda”; Note: principal investigator at UC. Abstract: The goal of this project is the realization of research and development (R&D) in the areas if computational intelligence, virtual sensors, estimation, monitoring, prediction, diagnosis, and control applied to waste water treatment plants (WWTP). 1. LRN2002 - Learning Methods for Robot Operation Reference number: POSI/SRI/42043/2001; Host institution: “Institute of Systems and Robotics - University of Coimbra” (ISR-UC); Start date: 2002/05/01; End date: 2005/12/31; Financing: Fundação para a Ciência e a Tecnologia (FCT). Abstract: This project addresses learning methods for mobile robots. Some example-applications of the mobile robots are: robots for service buildings such as hospitals and offices, human-oriented robots, factory mobile robots, automated car driving, autonomous transportation systems for cities, and planetary and underwater exploration. The available sensor technologies give the possibility to equip robots to have a better understanding of the surrounding world. However, robots must perceive useful information from raw sensor data, and learn models of the world for better deciding its actions according to its objectives. Learning techniques provide autonomy and flexibility on the creation of robot control competencies, and decreasing the need for a priori models of the robot, world, and robot world interactions. Additionally, learning only relevant aspects of the world can decrease computational overheads and complexity. Intelligent algorithms and paradigms, based on Fuzzy Logic, Neural Networks, supervised learning, self-organizing learning, reinforcement learning, memory-based learning, or other techniques, are being investigated and developed enabling robots to learn, navigate, plan and behave in the real world. Kalman estimators and energy minimization methods can be powerful tools for adjusting learned models. The main goal of this project is to expand the research from a navigation architecture previously developed by the team. For this purpose, at the world model level, it will be developed a multi-resolution memory-based method and a self-organizing neural network that will be used for implementing a map learning method for dynamic worlds. An important aspect for a mobile robot is the knowledge of its own location in the environment. This is crucial for learning the world model and for planning robot motions. An objective of this project is to perform research towards the integration into our navigation architecture of a method for mobile robot localization. Another goal of this project is to investigate how to integrate in our navigation architecture methods for learning robot behaviors with tightly-coupled sensing and action information. Applying reinforcement learning and supervised learning modules for learning in continuous spaces is an interesting and challenging research subject. With the work of this project we aim to investigate methods and algorithms towards the development of intelligent robots which presently are still very far from our needs, in spite of the big developments of science and engineering, Team Member in R&D Projects:
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