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  • 1.
    Aaltonen, Harri
    et al.
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Sierla, Seppo
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Kyrki, Ville
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Pourakbari-Kasmaei, Mahdi
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Bidding a Battery on Electricity Markets and Minimizing Battery Aging Costs: A Reinforcement Learning Approach2022In: Energies, E-ISSN 1996-1073, Vol. 15, no 14, article id 4960Article in journal (Refereed)
    Abstract [en]

    Battery storage is emerging as a key component of intelligent green electricitiy systems. The battery is monetized through market participation, which usually involves bidding. Bidding is a multi‐objective optimization problem, involving targets such as maximizing market compensation and minimizing penalties for failing to provide the service and costs for battery aging. In this article, battery participation is investigated on primary frequency reserve markets. Reinforcement learning is applied for the optimization. In previous research, only simplified formulations of battery aging have been used in the reinforcement learning formulation, so it is unclear how the optimizer would perform with a real battery. In this article, a physics‐based battery aging model is used to assess the aging. The contribution of this article is a methodology involving a realistic battery simulation to assess the performance of the trained RL agent with respect to battery aging in order to inform the selection of the weighting of the aging term in the RL reward formula. The RL agent performs day-ahead bidding on the Finnish Frequency Containment Reserves for Normal Operation market, with the objective of maximizing market compensation, minimizing market penalties and minimizing aging costs.

  • 2.
    Aaltonen, Harri
    et al.
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Sierla, Seppo
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Subramanya, Rakshith
    Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, School of Electrical Engineering, Aalto University, FI-00076 Espoo, Finland; International Research Laboratory of Computer Technologies, ITMO University, 197101 St. Petersburg, Russia.
    A simulation environment for training a reinforcement learning agent trading a battery storage2021In: Energies, E-ISSN 1996-1073, Vol. 14, no 17, article id 5587Article in journal (Refereed)
    Abstract [en]

    Battery storages are an essential element of the emerging smart grid. Compared to other distributed intelligent energy resources, batteries have the advantage of being able to rapidly react to events such as renewable generation fluctuations or grid disturbances. There is a lack of research on ways to profitably exploit this ability. Any solution needs to consider rapid electrical phenomena as well as the much slower dynamics of relevant electricity markets. Reinforcement learning is a branch of artificial intelligence that has shown promise in optimizing complex problems involving uncertainty. This article applies reinforcement learning to the problem of trading batteries. The problem involves two timescales, both of which are important for profitability. Firstly, trading the battery capacity must occur on the timescale of the chosen electricity markets. Secondly, the real-time operation of the battery must ensure that no financial penalties are incurred from failing to meet the technical specification. The trading-related decisions must be done under uncertainties, such as unknown future market prices and unpredictable power grid disturbances. In this article, a simulation model of a battery system is proposed as the environment to train a reinforcement learning agent to make such decisions. The system is demonstrated with an application of the battery to Finnish primary frequency reserve markets.

  • 3.
    Abrishambaf, Reza
    et al.
    Department of Engineering Technology, Miami University, Hamilton, OH.
    Bal, Mert
    Department of Engineering Technology, Miami University, Hamilton, OH.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Distributed home automation system based on IEC61499 function blocks and wireless sensor networks2017In: Proceedings of the IEEE International Conference on Industrial Technology, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 1354-1359, article id 7915561Conference paper (Refereed)
    Abstract [en]

    In this paper, a distributed home automation system will be demonstrated. Traditional systems are based on a central controller where all the decisions are made. The proposed control architecture is a solution to overcome the problems such as the lack of flexibility and re-configurability that most of the conventional systems have. This has been achieved by employing a method based on the new IEC 61499 function block standard, which is proposed for distributed control systems. This paper also proposes a wireless sensor network as the system infrastructure in addition to the function blocks in order to implement the Internet-of-Things technology into the area of home automation as a solution for distributed monitoring and control. The proposed system has been implemented in both Cyber (nxtControl) and Physical (Contiki-OS) level to show the applicability of the solution

  • 4.
    Akifev, Daniil
    et al.
    Independent researcher.
    Liakh, Tatiana
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Ovsiannikova, Polina
    Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Sorokin, Radimir
    Independent researcher.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Debugging approach for IEC 61499 control applications in FBME2023In: 2023 IEEE 32nd International Symposium on Industrial Electronics (ISIE), IEEE, 2023Conference paper (Refereed)
  • 5.
    Alsafi, Yazen
    et al.
    University of Auckland, School of Electrical and Computer Engineering.
    Vyatkin, Valeriy
    A deployment of an ontology-based reconfiguration agent for intelligent mechatronic systems2008In: ISIE08: 2008 IEEE International Symposium on Industrial Electronics : [Cambridge, UK, June 30 to July 2, 2008], Piscataway, NJ: IEEE Communications Society, 2008, p. 1780-1785Conference paper (Refereed)
    Abstract [en]

    This paper discusses the extension of an ontology-based reconfiguration agent that uses ontological knowledge of the manufacturing environment for the purpose of reconfiguration without human intervention. The current mass customization era requires increased flexibility and agility in the manufacturing systems to adapt changes in manufacturing requirements and environments. Our configuration agent minimises the overheads of the current reconfiguration process by automating it. It infers facts about the manufacturing environment from the ontological knowledge model and then decides whether the current environment can support the given manufacturing requirements. This paper proposes an extension of the agent architecture enabling the integration between the high level planning with the distributed low level control compliant with the upcoming IEC 61499 function blocks standard

  • 6.
    Al-Safi, Yazen
    et al.
    University of Auckland, School of Electrical and Computer Engineering.
    Vyatkin, Valeriy
    An ontology-based reconfiguration agent for intelligent mechatronic systems2007In: Holonic and multi-agent systems for manufacturing: third International Conference on Industrial Applications of Holonic and Multi-Agent Systems, HoloMAS 2007, Regensburg, Germany, September 3-5, 2007 ; proceedings / [ed] Vladimir Mařik ; Valeriy Vyatkin ; Armando Walter Colombo, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2007, p. 114-126Conference paper (Refereed)
    Abstract [en]

    This paper discusses an ontology-based reconfiguration agent that uses ontological knowledge of the manufacturing environment for the purpose of reconfiguration without human intervention. The current mass customization era requires increased flexibility and agility in the manufacturing systems to adapt changes in manufacturing requirements and environments. Our configuration agent minimizes the overheads of the current reconfiguration process by automating it. It infers facts about the manufacturing environment from the ontological knowledge model and then decides whemer the current environment can support the given manufacturing requirements

  • 7.
    Alsafi, Yazen
    et al.
    University of Auckland, Department of Electrical and Computer Engineering, Auckland Mail Centre.
    Vyatkin, Valeriy
    Ontology-based reconfiguration agent for intelligent mechatronic systems in flexible manufacturing2010In: Robotics and Computer-Integrated Manufacturing, ISSN 0736-5845, E-ISSN 1879-2537, Vol. 26, no 4, p. 381-391Article in journal (Refereed)
    Abstract [en]

    This paper proposes a novel approach to achieving fast reconfiguration of modular manufacturing systems, based on an ontology-based reconfiguration agent. The agent uses ontological knowledge of the manufacturing environment for the purpose of reconfiguration without human intervention. The current mass customization era requires increased flexibility and agility in the manufacturing systems to adapt changes in manufacturing requirements and environments. Our configuration agent minimises the overheads of the current reconfiguration process by automating it. It infers facts about the manufacturing environment from the ontological knowledge model and then decides whether the current environment can support the given manufacturing requirements. This paper proposes the agent architecture enabling the integration between the high level planning with the distributed low level control compliant with the upcoming IEC 61499 function blocks standard

  • 8.
    Altmojo, Udayanto Dwi
    et al.
    Aalto Univ, Dept Elect Engn & Automat, Aalto, Finland.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Aalto Univ, Dept Elect Engn & Automat, Espoo, Finland.
    Salcic, Zoran
    Univ Auckland, Dept Elect & Comp Engn, Auckland, New Zealand.
    On Achieving Reliable Communication in IEC 614992018In: 2018 IEEE 23RD INTERNATIONAL CONFERENCE ON EMERGING TECHNOLOGIES AND FACTORY AUTOMATION (ETFA), Piscataway, NJ: IEEE, 2018, p. 147-154Conference paper (Refereed)
    Abstract [en]

    This paper proposes a novel extension for communication in the IEC 61499 standard. Inspired by the features found in the formal programming language SystemJ, the extension supports reliable and guaranteed communication in distributed execution of function block application(s)/program(s). The extension utilizes mechanisms agnostic on underlying network protocols and are based on formal semantics that guarantee data delivery. The use of proposed extension, called channel, is demonstrated in an industrial automation-type example.

  • 9.
    Atmojo, Udayanto Dwi
    et al.
    Department of Electrical Engineering and Automation, Aalto University.
    Gulzar, Kashif
    Department of Electrical Engineering and Automation, Aalto University.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University.
    Ma, Rongwei
    Department of Electrical Engineering and Automation, Aalto University.
    Hopsu, Alexander
    Department of Electrical Engineering and Automation, Aalto University.
    Makkonen, Henri
    Department of Electrical Engineering and Automation, Aalto University.
    Korhonen, Atte
    Department of Electrical Engineering and Automation, Aalto University.
    Phu, Long Tran
    Department of Electrical Engineering and Automation, Aalto University.
    Distributed control architecture for dynamic reconfiguration: Flexible assembly line case study2018Conference paper (Refereed)
    Abstract [en]

    This article presents the development of a distributed manufacturing case study enhanced with features that enable flexibility during the production process and the capability to continue the production process in case of fault scenarios. The approach described in this paper presents solutions to achieve the production of customized products, handle changes in product order, and minimize downtime and avoid total shutdown of the manufacturing system due to the occurrence of failures during the production process.

  • 10.
    Atmojo, Udayanto Dwi
    et al.
    Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Salcic, Zoran
    Electrical and Computer Engineering, The University of Auckland, Auckland, New Zealand.
    Wang, Kevin I-Kai
    The University of Auckland, 1415 Auckland, New Zealand .
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Automation, Aalto University, Espoo, Finland.
    A Service-Oriented Programming Approach for Dynamic Distributed Manufacturing Systems2020In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 16, no 1, p. 150-160Article in journal (Refereed)
    Abstract [en]

    Dynamic reconfigurability and adaptability are crucial features of the future manufacturing systems that must be supported by adequate software technologies. Currently, they are typically achieved as add-ons to existing software tools and run-time systems, which are not based on any formal foundation such as formal model of computation (MoC). This paper presents the new programming paradigm of Service Oriented SystemJ (SOSJ), which targets dynamic distributed software systems suited for future manufacturing applications. SOSJ is built on a merger and the synergies of two programming concepts of (1) Service Oriented Architecture (SOA), to support dynamic software system composition, and (2) SystemJ programming language based on a formal MoC, which targets correct by construction design of static distributed software systems. The resulting programming paradigm allows the design and implementation of dynamic distributed software systems.

  • 11.
    Atmojo, Udayanto Dwi
    et al.
    Dept. of Electrical Engineering and Automation, Aalto University, Finland.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Dept. of Electrical Engineering and Automation, Aalto University, Finland.
    A Design Pattern for Systems Composed from Intelligent Mechatronic Modules with Wireless Communication2019In: Proceedings: 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 2019, p. 41-48Conference paper (Refereed)
    Abstract [en]

    This paper presents a software design pattern for systems composed from distributed intelligent mechatronic modules which communicate with each other via wireless interface. The design pattern is formed by integrating the reliable communication mechanism called channel, which comes from a system-level programming language SystemJ. The paper demonstrates how the design pattern can be applied in an industrial automation example.

  • 12.
    Auinger, Franz
    et al.
    University for Applied Science Wels, Industrial Informatics.
    Brennan, Robert William
    University of Calgary, Department of Mechanical and Manufacturing Engineerin.
    Christensen, James H.
    Rockwell Automation Advanced Technologies, Mayfield Heights.
    Lastra, José Luis Martínez
    Tampere University of Technology, Institute of Production Engineering.
    Vyatkin, Valeriy
    Requirements and solutions to software encapsulation and engineering in next generation manufacturing systems: OOONEIDA approach2005In: International journal of computer integrated manufacturing (Print), ISSN 0951-192X, E-ISSN 1362-3052, Vol. 18, no 7, p. 572-585Article in journal (Refereed)
    Abstract [en]

    This paper addresses the solutions enabling agile development, deployment and re-configuration of software-intensive automation systems both in discrete manufacturing and process technologies. As the key enabler for reaching the required level of flexibility of such systems, the paper discusses the issues of encapsulation, integration and re-use of the automation intellectual property (IP). The goals can be fulfilled by the use of a vendor-independent concept of a reusable portable and scalable software module (function block), as well as by a vendor-independent automation device model. This paper also discusses the requirements of the methodology for the application of such modules in the time- and cost-effective specification, design, validation, realization and deployment of intelligent mechatronic components in distributed industrial automation and control systems. A new global initiative OOONEIDA is presented, that targets these goals through the development of the automation object concept based on the recognized industrial standards IEC61131, IEC61499, IEC61804 and unified modelling language (UML); and through the creation of the technological infrastructure for a new, open-knowledge economy for automation components and automated industrial products. In particular, a web-based repository for standardized automation solutions will be developed to serve as an electronic-commerce facility in industrial automation businesses.

  • 13.
    Azangoo, Mohammad
    et al.
    Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Blech, Jan Olaf
    Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Atmojo, Udayanto Dwi
    Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Dhakal, Kamal
    Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Eriksson, Mikael
    Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Lehtimäki, Miika
    Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Leinola, Jonathan
    Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Pietarila, Pyry
    Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Towards a 3D Scanning/VR-based Product Inspection Station2020In: Proceedings: 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 2020, p. 1263-1266Conference paper (Refereed)
    Abstract [en]

    Quality control of products plays an important role in various stages of the manufacturing process. In particular the final control of the quality of a product before being shipped to a customer is crucial for maintaining customer satisfaction and avoiding costly recalls. Automating quality inspection and integrating it into a seamless Industry 4.0 setting is therefore an important topic in factory automation.We present early work towards an automated product inspection station. Our inspection station features a 3D scanner as well as a Virtual Reality headset for remote human inspection. In addition, our concept provides for automated analysis of scans in the cloud. We present an architectural concept as well as an early prototype.

  • 14.
    Azangoo, Mohammad
    et al.
    Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Salmi, Joonas
    Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Yrjöla, Iivo
    Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Bensky, Jonathan
    Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Santillan, Gerardo
    Semantum Oy, Espoo, Finland.
    Papakonstantinou, Nikolaos
    VTT Technical Research Centre of Finland Ltd, Espoo, Finland.
    Sierla, Seppo
    Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Hybrid Digital Twin for process industry using Apros simulation environment2021In: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 2021Conference paper (Refereed)
    Abstract [en]

    Making an updated and as-built model plays an important role in the life-cycle of a process plant. In particular, Digital Twin models must be precise to guarantee the efficiency and reliability of the systems. Data-driven models can simulate the latest behavior of the sub-systems by considering uncertainties and life-cycle related changes. This paper presents a step-by-step concept for hybrid Digital Twin models of process plants using an early implemented prototype as an example. It will detail the steps for updating the first-principles model and Digital Twin of a brownfield process system using data-driven models of the process equipment. The challenges for generation of an as-built hybrid Digital Twin will also be discussed. With the help of process history data to teach Machine Learning models, the implemented Digital Twin can be continually improved over time and this work in progress can be further optimized.

  • 15.
    Azangoo, Mohammad
    et al.
    Department of Electrical Engineering and Automation, Aalto University, 00076 Helsinki, Finland.
    Sorsamäki, Lotta
    VTT Technical Research Center of Finland, 02044 Espoo, Finland.
    Sierla, Seppo
    Department of Electrical Engineering and Automation, Aalto University, 00076 Helsinki, Finland.
    Mätäsniemi, Teemu
    VTT Technical Research Center of Finland, 02044 Espoo, Finland.
    Rantala, Miia
    Semantum Oy, 02150 Espoo, Finland.
    Rainio, Kari
    VTT Technical Research Center of Finland, 02044 Espoo, Finland.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University, 00076 Helsinki, Finland.
    A methodology for generating a digital twin for process industry: a case study of a fiber processing pilot plant2022In: IEEE Access, E-ISSN 2169-3536, Vol. 10, p. 58787-58810Article in journal (Refereed)
    Abstract [en]

    Digital twins are now one of the top trends in Industry 4.0, and many companies are using them to increase their level of digitalization, and, as a result, their productivity and reliability. However, the development of digital twins is difficult, expensive, and time consuming. This article proposes a semi-automated methodology to generate digital twins for process plants by extracting process data from engineering documents using text and image processing techniques. The extracted information is used to build an intermediate graph model, which serves as a starting point for generating a model in a simulation software. The translation of a graph-based model into a simulation software environment necessitates the use of simulator-specific mapping rules. This paper describes an approach for generating a digital twin based on a steady state simulation model, using a Piping and Instrumentation Diagram (P&ID) as the main source of information. The steady state modeling paradigm is especially suitable for use cases involving retrofits for an operational process plant, also known as a brownfield plant. A methodology and toolchain is proposed, consisting of manual, semi-automated and fully automated steps. A pilot scale brownfield fiber processing plant was used as a case study to demonstrate our proposed methodology and toolchain, and to identify and address issues that may not occur in laboratory scale case studies. The article concludes with an evaluation of unresolved concerns and future research topics for the automated development of a digital twin for a brownfield process system.

  • 16.
    Azangoo, Mohammad
    et al.
    Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Taherkordi, Amir
    Department of Informatics, University of Oslo, Oslo, Norway.
    Blech, Jan Olaf
    Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Digital Twin-Assisted Controlling of AGVs in Flexible Manufacturing Environments2021In: 2021 IEEE 30th International Symposium on Industrial Electronics (ISIE), IEEE, 2021Conference paper (Refereed)
    Abstract [en]

    Digital Twins are increasingly being introduced for smart manufacturing systems to improve the efficiency of the main disciplines of such systems. Formal techniques, such as graphs, are a common way of describing Digital Twin models, allowing broad types of tools to provide Digital Twin based services such as fault detection in production lines. Obtaining correct and complete formal Digital Twins of physical systems can be a complicated and time consuming process, particularly for manufacturing systems with plenty of physical objects and the associated manufacturing processes. Automatic generation of Digital Twins is an emerging research field and can reduce time and costs. In this paper, we focus on the generation of Digital Twins for flexible manufacturing systems with Automated Guided Vehicles (AGVs) on the factory floor. In particular, we propose an architectural framework and the associated design choices and software development tools that facilitate automatic generation of Digital Twins for AGVs. Specifically, the scope of the generated digital twins is controlling AGVs in the factory floor. To this end, we focus on different control levels of AGVs and utilize graph theory to generate the graph-based Digital Twin of the factory floor.

  • 17. Bahadornejad, M.
    et al.
    Nair, N.C.
    Zhabelova, G.
    Vyatkin, Valeriy
    Modelling solid state transformer in IEC 618502011In: IECON 2011 - 37th Annual Conference on IEEE Industrial Electronics Society, IEEE Communications Society, 2011, p. 2706-2710Conference paper (Refereed)
  • 18.
    Baniya, Rupak
    et al.
    Department of Electrical Engineering, School of Electrical Engineering, Aalto University.
    Maksimainen, Mikko
    Department of Electrical Engineering, School of Electrical Engineering, Aalto University.
    Sierla, Seppo
    Department of Automation and Systems Technology, School of Electrical Engineering, Aalto University.
    Pang, Cheng
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Yang, Chen-Wei
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Smart indoor lighting control: power, illuminance, and colour quality2014In: Proceedings: 2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE) : Grand Cevahir Hotel and Convention Center Istambul, Turkey : 01 - 04 June, 2014, Piscataway, NJ: IEEE Communications Society, 2014, p. 1745-1750, article id 6864878Conference paper (Refereed)
    Abstract [en]

    This paper investigates the correlation between color quality and energy efficiency of indoor lighting control. The color quality, in terms of visual performance and comfort, is quantified using three measurements: illuminance, Color Rendering Index, and Correlated Color Temperature. Several experiments have been conducted to evaluate the potential energy savings of using different portions of light spectrum to obtain the optimal color quality. In particular, Light-Emitting Diodes are used as the lighting sources of the experimental luminaire. Moreover, the above quantification method and experimental results have been incorporated into a previously developed simulation framework for Building Automation and Control Systems, and smart lighting is used to adjust the tradeoff between comfort and energy consumption based on the presence of occupants. The results can be used to evaluate the viability of advanced lighting automation.

    Download full text (pdf)
    FULLTEXT01
  • 19.
    Barni, Andrea
    et al.
    Scuola Universitaria Professionale della Svizzera Italiana - SUPSI, Manno, Switzerland.
    Brusaferri, Alessandro
    Consiglio Nazionale delle Ricerche - CNR-STIIMA, Milan, Italy.
    Cavadini, Franco A.
    SYNESIS s.c.a.r.l., Lomazzo, Italy.
    Landolf, Giuseppe
    Scuola Universitaria Professionale della Svizzera Italiana - SUPSI, Manno, Switzerland.
    Patil, Sandeep
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Piga, Dario
    Scuola Universitaria Professionale della Svizzera Italiana - SUPSI, Manno, Switzerland.
    Spinelli, Stefano
    Consiglio Nazionale delle Ricerche - CNR-STIIMA, Milan, Italy.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Fostering the creation of a Digital Ecosystem by a distributed IEC-61499 based automation platform2019In: 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), IEEE, 2019, p. 635-640Conference paper (Other academic)
    Abstract [en]

    Daedalus is conceived to enable the full exploitation of the CPS' virtualized intelligence concept, through the adoption of a completely distributed automation platform based on IEC-61499 standard, fostering the creation of a Digital Ecosystem that could go beyond the current limits of manufacturing control systems and propose an ever-growing market of innovative solutions for the design, engineering, production and maintenance of plants' automation.

  • 20.
    Bejarano, Ronal
    et al.
    School of Electrical Engineering, Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Atmojo, Udayanto Dwi
    School of Electrical Engineering, Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Blech, Jan Olaf
    School of Electrical Engineering, Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Towards enhanced live visualization based on communication delay prediction for remote AGV operation2021In: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 2021, p. 01-04Conference paper (Refereed)
    Abstract [en]

    This paper presents the development progress of a methodology to enhance the dynamic visualization of remote Automated Guided Vehicles (AGVs) using open source frameworks as Gazebo and ROS. The approach is based on a deterministic path pre-calculated by edge computing, accessible for a 3D web visualization cloud platform. The trajectory displayed is verified by a live position streaming from the AGV and a predicted communication delay value. By succeeding on the methodology proposed, it is expected to enhance the fidelity of the 3D live representation for every trajectory executed dynamically and autonomously by AGVs in the shop floor, leaving behind an initial scenario with low visualization fidelity due non-deterministic behavior of long-distance communication channels (including wireless networks essential for AGVs). This work aims to have an impact on improving the user experience of remote webbased interfacing tools to visualize the behavior of cyber-physical systems in agile manufacturing.

  • 21.
    Bejarano, Ronal
    et al.
    School of Electrical Engineering, Aalto University, Espoo, Finland.
    Päkkönen, Roope
    School of Electrical Engineering, Aalto University, Espoo, Finland.
    Blech, Jan Olaf
    School of Electrical Engineering, Aalto University, Espoo, Finland.
    Peake, Ian
    RMIT University, Melbourne, Australia.
    Herrmann, Peter
    Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. School of Electrical Engineering, Aalto University, Espoo, Finland.
    Assessing Long Distance Communication Alternatives for the Remote Control of AGVs2020In: Proceedings: 2020 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), IEEE, 2020, p. 69-76Conference paper (Refereed)
    Abstract [en]

    Remote monitoring and control of factory equipment promises a more streamlined and therefore less expensive system operation and maintenance. The geographical distance between a factory and its control center, however, may influence the Quality of Service parameters of the network connections which might stymie the overall control process. To get a better understanding of these potential issues and their impact, we conducted a series of measurements over varying distances for the remote control, operation and simulation of Automated Guided Vehicles (AGVs) that are often used in modern factory environments. To achieve these tests, we defined three communication patterns reflecting local and remote connections as well as the usage of cloud-based services. Applying these patterns, we connected the Factory of the Future at the Aalto University in Finland with the VxLab at the RMIT University in Australia and the Microsoft Azure cloud in the Netherlands. This allowed us to measure important Quality of Service networking parameters for the communication over short, medium, and very long distances. In this paper, we present first empirical results and discuss their impact on the remote control of AGVs.

  • 22.
    Belyakov, Stanislav Leonidovich
    et al.
    Southern Federal University, Department of Applied Information Science Taganrog.
    Savelyeva, Marina
    Southern Federal University, Department of Applied Information Science Taganrog.
    Yan, Jeffrey
    Department of Electrical and Computer System Engineering, University of Auckland, University of Auckland.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Adaptation of Material Flows in Mechanical Transportation Systems Based on Observation Experience2015In: IEEE TrustCom-BigDataSE-ISPA 2015: Helsinki, 20-22 Aug. 2015, Piscataway, NJ: IEEE Communications Society, 2015, p. 269-274, article id 7345659Conference paper (Refereed)
    Abstract [en]

    This paper investigates adaptation of material flows in mechanical transportation systems to the appearance of local overloads. The adaptation mechanism is based on the deflection of the forecast of experts who oversee the behavior of flows in the network. We propose a modified version of case-based reasoning, which uses the concept of imagination of situations. Unlike known methods, imaginative description of cases increases the reliability of decision-making. We provide a modification of the algorithm for dynamically building routing tables in distributed controllers of a transportation network. Analytic evaluation of the adaptation method's effectiveness is provided. The paper is concluded with outline of the implementation mechanism using a network of distributed controllers

  • 23.
    Belyakov, Stanislav Leonidovich
    et al.
    Southern Federal University, Department of Applied Information Science Taganrog.
    Savelyeva, Marina
    Southern Federal University, Department of Applied Information Science Taganrog.
    Yan, Jeffrey
    Department of Electrical and Computer System Engineering, University of Auckland, University of Auckland.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Knowledge-based routing in mechanical transportation systems2014In: 12th IEEE International Conference on Industrial Informatics, INDIN 2014: Porto Alegre, Brazil, 27 - 30 July 2014, Piscataway, NJ: IEEE Communications Society, 2014, p. 48-53Conference paper (Refereed)
    Abstract [en]

    This paper presents the ways of constructing routing algorithms in mechanical transport systems based on knowledge. It is assumed that the experts observing system behavior applies his experience by designating subsystems with a specific behavior. To create routing tables, a model of fuzzy temporal hypergraph was used. We consider fixed and dynamic routing, given modifications of Dijkstra's algorithm for the case of fuzzy temporal hypergraphs

  • 24.
    Berezovskaya, Yulia
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Mousavi, Arash
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University, Finland.
    Zhang, Xiaojing
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. ABB Corporate Research, Västerås, Sweden .
    Smart Distribution of IT Load in Energy Efficient Data Centers with Focus on Cooling Systems2018In: Proceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society, IEEE, 2018, p. 4907-4912Conference paper (Refereed)
    Abstract [en]

    Cooling system is the second most energy-consuming part of a modern data center; herewith it often consumes energy inefficiently. Therefore, any possibility allowing to reduce energy consumption of cooling systems should be studied and put into practice if successful. In this paper, the idea about impact of IT load distribution between servers on energy consumption of data center cooling system is proposed. The idea is in distribution of total IT load between servers according to the location of the servers inside racks. To test idea, the model simulating the thermal behaviour and energy consumption of a real data center located in Northern Sweden is developed. Comparing the data obtained from the real plant and the data generated at the simulation shows the reliability of the model. Two strategies of IT load distribution between servers are considered, and their impact on energy consumption of cooling system is demonstrated.

  • 25.
    Berezovskaya, Yulia
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Mousavi, Arash
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Zhang, Xiaojing
    ABB Corporate Research, Västerås, Sweden.
    Minde, Tor Björn
    SICS Swedish ICT, Luleå, Sweden.
    Improvement of Energy Efficiency in Data Centers via Flexible Humidity Control2016In: IECON Proceedings (Industrial Electronics Conference), Piscataway, NJ: IEEE Computer Society, 2016, p. 5585-5590, article id 7793777Conference paper (Refereed)
    Abstract [en]

    Abstract- The main goal of climate control systems in data centres is to keep the temperature and humidity in a suitable level for computational devices. Therefore, cooling and humidification systems are essential parts of every Building Automation System (BAS), which is utilized in server rooms. Although the current climate control systems ensure appropriate thermal conditions to computational nodes such as servers, they waste substantial amount of energy. The main cause of this inefficiency is that the current climate control systems, which are responsible for thermal management of the data centres, follow rigid control strategies that maintain constant thermal conditions irrespective of climate changes caused by various computational loads in the plant. To address this issue, in our previous works we proposed a method of optimizing energy consumption in data centre cooling systems while maintaining an acceptable level of thermal comfort for CPUs in the server room. In this paper, we present the enhancement of our previous method by incorporating humidity control into it. The enhanced method consists of a thermal model of server room, and a simulation tool to find an energy efficient control strategy for the climate control system in different situations by comparing different control strategies. The effectiveness of the proposed method has been investigated via simulation and the result, which shows 41.5% reduction in total energy consumption is presented.

  • 26.
    Berezovskaya, Yulia
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Yang, Chen-Wei
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Mousavi, Arash
    IT Department, SCANIA CV AB, Södertälje, Sweden.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University, 02150 Helsinki, Finland.
    Minde, Tor Björn
    RISE SICS North, Luleå, Sweden.
    Modular Model of a Data Centre as a Tool for Improving Its Energy Efficiency2020In: IEEE Access, E-ISSN 2169-3536, Vol. 8, p. 46559-46573Article in journal (Refereed)
    Abstract [en]

    For most modern data centres, it is of high value to select practical methods for improving energy efficiency and reducing energy waste. IT-equipment and cooling systems are the two most significant energy consumers in data centres, thus the energy efficiency of any data centre mainly relies on the energy efficiency of its computational and cooling systems. Existing techniques of optimising the energy usage of both these systems have to be compared. However, such experiments cannot be conducted in real plants as they may harm the electronic equipment. This paper proposes a modelling toolbox which enables building models of data centres of any scale and configuration with relative ease. The toolbox is implemented as a set of building blocks which model individual components of a typical data centre, such as processors, local fans, servers, units of cooling systems, it provides methods of adjusting the internal parameters of the building blocks, as well as contains constructors utilising the building blocks for building models of data centre systems of different levels from server to the server room. The data centre model is meant to accurate estimating the energy consumption as well as the evolution of the temperature of all computational nodes and the air temperature inside the data centre. The constructed model capable of substitute for the real data centre at examining the performance of different energy-saving strategies in dynamic mode: the model provides information about data centre operating states at each time point (as model outputs) and takes values of adjustable parameters as the control signals from system implementing energy-saving algorithm (as model inputs). For Module 1 of the SICS ICE data centre located in Luleå, Sweden, the model was constructed from the building blocks. After adjusting the internal parameters of the building blocks, the model demonstrated the behaviour quite close to real data from the SICS ICE data centre. Therefore the model is applicable to use as a substitute for the real data centre. Some examples of using the model for testing energy-saving strategies are presented at the end of the paper.

  • 27.
    Berezovskaya, Yulia
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Yang, Chen-Wei
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Mousavi, Arash
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Zhang, Xiaojing
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. ABB Corporate Research, Västerås, Sweden.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University, Finland .
    A hybrid fault detection and diagnosis method in server rooms’ cooling systems2019In: 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), IEEE, 2019, p. 1405-1410Conference paper (Other academic)
    Abstract [en]

    Data centers as all complex systems are prone to faults, and cost of them can be very high. This paper is focused on detecting the faults in the cooling systems, in particular on local fans level. In the paper, a hybrid approach is proposed. In the approach a model is used as substitute of the real system to generate dataset containing records of both normal and fault cases. On the generated data, machine learning algorithm or ensemble of algorithms are selected and trained to detect the faults. To demonstrate the approach, the rack model of real data center is created, and reliability of the model is shown. Using the model, the dataset with normal as well as abnormal records of data is generated. To detect faults of local fans, simple classifiers are built for all pairs: a local fan – a processor unit. Classifiers are trained on one part of generated data (training data), and then their accuracy is estimated on another part of generated data (test data). A real-time fault detection system is built based on the classifiers. The rack model is used as the substitute of the real plant to check operability of the system.

  • 28.
    Berezovskaya, Yulia
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Yang, Chen-Wei
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Reinforcement learning approach to implementation of individual controllers in data centre control system2022In: 2022 IEEE 20th International Conference on Industrial Informatics (INDIN), IEEE, 2022, p. 41-46Conference paper (Refereed)
    Abstract [en]

    Contemporary data centres consume electricity onan industrial scale and require control to improve energyefficiency and maintain high availability. The article proposes anidea and structure of the framework supporting development andvalidation of the multi-agent control for the energy-efficient datacentre. The framework comprises two subsystems: the modellingtoolbox and the controlling toolbox. This work focuses on suchessential components of the controlling toolbox, as an individualcontroller. The reinforcement learning approach is applied to thecontrollers’ implementation. The server fan controller, named SFagent, is implemented based on the framework infrastructureand reinforcement learning approach. The agent’s capability ofenergy-saving is demonstrated.

  • 29.
    Berezovskaya, Yulia
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Yang, Chen-Wei
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University, Espoo, Finland.
    Towards Extension of Data Centre Modelling Toolbox with Parameters Estimation2021In: Technological Innovation for Applied AI Systems: 12th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2021, Costa de Caparica, Portugal, July 7–9, 2021, Proceedings / [ed] Luis M. Camarinha-Matos; Pedro Ferreira; Guilherme Brito, Springer, 2021, p. 189-196Conference paper (Refereed)
    Abstract [en]

    Modern data centres consume a significant amount of electricity. Therefore, they require techniques for improving energy efficiency and reducing energy waste. The promising energy-saving methods are those, which adapt the system energy use based on resource requirements at run-time. These techniques require testing their performance, reliability and effect on power consumption in data centres. Generally, real data centres cannot be used as a test site because of such experiments may violate safety and security protocols. Therefore, examining the performance of different energy-saving strategies requires a model, which can replace the real data centre. The model is expected to accurately estimate the energy consumption of data centre components depending on their utilisation. This work presents a toolbox for data centre modelling. The toolbox is a set of building blocks representing individual components of a typical data centre. The paper concentrates on parameter estimation methods, which use data, collected from a real data centre and adjust parameters of building blocks so that the model represents the data centre most accurately. The paper also demonstrates the results of parameters estimation on an example of EDGE module of SICS ICE data centre located in Luleå, Sweden. 

  • 30.
    Berezovskaya, Yulia
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Yang, Chen-Wei
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University, Finland .
    Towards Multi-Agent Control in Energy-Efficient Data Centres2020In: Proceedings: IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society, IEEE, 2020, p. 3574-3579Conference paper (Refereed)
    Abstract [en]

    Modern data centres consume electricity at the industrial scale; at the same time, most of them demonstrate redundancy in energy consumption. The two most significant energy consumers in a data centre are its computational system and cooling system. This work focuses on techniques, which adapt the system energy use based on resource requirements at run-time. Actually, this work is an inception phase, which determines the main requirements to control the energy-efficient data centre and develops its general project. For that aim, the general design of the multi-agent control is proposed. The different types of agents are identified and their objectives are determined. Based on agent types the architecture of the multi-agent control is developed and agents' interactions are considered. The paper presents an example of an agent controlling a server fan. The agent is examined using closed-loop co-simulation with a server model.

  • 31.
    Berezovskaya, Yulia
    et al.
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Yang, Chen-Wei
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Aalto University, Helsinki, Finland.
    Towards reinforcement learning approach to energy-efficient control of server fans in data centres2021In: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA ), IEEE, 2021, p. 1-4Conference paper (Refereed)
    Abstract [en]

    Modern data centres require control, which aims to improve their energy efficiency and maintain their high availability. This work considers the implementation of a server fan agent, which is intended to minimise the power consumption of the corresponding server fan or group of fans. In the paper, the reinforcement learning approach to energy-efficient control of server fans is suggested. The reinforcement learning workflow is considered. The Simulink blocks simplifying the building of the environment for the reinforcement learning agent are developed. This work provides the framework for creating and training reinforcement learning agents of different types. As the paper is only a work-in-progress, possible type of agents and their training process is described, but training and deploying the agent is a work for the future.

  • 32.
    Black, Geoff
    et al.
    University of Auckland.
    Vyatkin, Valeriy
    Intelligent component-based automation of baggage handling systems with IEC 614992010In: IEEE Transactions on Automation Science and Engineering, ISSN 1545-5955, E-ISSN 1558-3783, Vol. 7, no 2, p. 337-351Article in journal (Refereed)
    Abstract [en]

    Airport baggage handling is a field of automation systems that is currently dependent on centralized control systems and conventional automation programming techniques. In this and other areas of manufacturing and materials handling, these legacy automation technologies are increasingly limiting for the growing demand for systems that are reconfigurable, fault tolerant, and easy to maintain. IEC 61499 Function Blocks is an emerging architectural framework for the design of distributed industrial automation systems and their reusable components. A number of architectures have been suggested for multiagent and holonic control systems that incorporate function blocks. This paper presents a multiagent control approach for a baggage handling system (BHS) using IEC 61499 Function Blocks. In particular, it focuses on demonstrating a decentralized control system that is scalable, reconfigurable, and fault tolerant. The design follows the automation object approach, and produces a function block component representing a single section of conveyor. In accordance with holonic principles, this component is autonomous and collaborative, such that the structure and the behavior of a BHS can be entirely defined by the interconnection of these components within the function block design environment. Simulation is used to demonstrate the effectiveness of the agent-based control system and a utility is presented for real-time viewing of these systems. Tests on a physical conveyor test system demonstrated deployment to embedded control hardware.

  • 33.
    Black, Geoff
    et al.
    Department of Electrical and Computer Engineering, University of Auckland.
    Vyatkin, Valeriy
    On practical implementation of holonic control principles in baggage handling systems using IEC 614992007In: Holonic and multi-agent systems for manufacturing: third International Conference on Industrial Applications of Holonic and Multi-Agent Systems, HoloMAS 2007, Regensburg, Germany, September 3-5, 2007 ; proceedings / [ed] Vladimir Mařik ; Valeriy Vyatkin ; Armando Walter Colombo, Berlin: Encyclopedia of Global Archaeology/Springer Verlag, 2007, p. 314-325Conference paper (Refereed)
    Abstract [en]

    IEC 61499 Functional Blocks is an upcoming architectural framework for the design of complete distributed industrial automation systems and their reusable components. This paper presents a multi-agent distributed control approach for a baggage handling system using IEC 61499 Functional Blocks. In particular, it focuses on demonstrating a distributed control system that is scalable, reconfigurable and fault tolerant. The design follows the Automation Object approach, which ends up in a functional block representing a single section of conveyor, such that the structure (and consequently the behaviour) of the conveyor network is entirely defined by the interconnection of these blocks within the IEC 61499 design environment. The use of distributed simulation to achieve predictive control is demonstrated as a part of the control system design.

  • 34.
    Blech, Jan Olaf
    et al.
    RMIT University, Melbourne.
    Lindgren, Per
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Embedded Internet Systems Lab.
    Pereira, David
    ISEP, Instituto Superior de Engenharia do Porto.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Zoitl, Alois
    fortiss GmbH, Munich.
    A Comparison of Formal Verification Approaches for IEC 614992016In: 2016 IEEE 21st International Conference on Emerging Technologies and Factory Automation (ETFA): Berlin, 6-9 Sept. 2016, Piscataway, NJ: IEEE conference proceedings, 2016, article id 7733636Conference paper (Refereed)
    Abstract [en]

    Engineering and computer science have come up with a variety of techniques to increase the confidence in systems, increase reliability, facilitate certification, improve reuse and maintainability, improve interoperability and portability. Among them are various techniques based on formal models to enhance testing, validation and verification. In this paper, we are concentrating on formal verification both at runtime and design time of a system. Formal verification of a system property at design time is the process of mathematically proving that the property indeed holds. At runtime, one can check the validity of the property and report deviations by monitoring the system execution. Formal verification relies on semantic models, descriptions of the system and its properties. We report on ongoing verification work and present two different approaches for formal verification of IEC 61499-based programs. We provide two examples of ongoing work to exemplify the design and the runtime verification approaches

  • 35.
    Bouzon, Gustavo
    et al.
    Department of Automation and Systems, Federal University of Santa Catarina.
    Vyatkin, Valeriy
    Hanisch, Hans Michael
    Department of Engineering Sciences, Martin Luther University Halle-Wittenberg.
    Timing diagram specifications in modular modeling of industrial automation systems2005In: Proceedings of the 16th IFAC world congress: Prague, Czech Republic, July 3 - 8, 2005, Oxford: Elsevier, 2005, p. 80-85Conference paper (Refereed)
    Abstract [en]

    This paper deals with further development of the timing-diagram based specification language destined for application in modular modeling of industrial automation systems. The results of this work are intended for application in formal verification of software intensive automation systems

  • 36.
    Budhia, Mickel
    et al.
    Department of Electrical and Computer Engineering, University of Auckland.
    Vyatkin, Valeriy
    Covic, Grant Anthony
    Department of Electrical and Computer Engineering, University of Auckland.
    Powering flexible manufacturing systems with intelligent contact-less power transfer2008In: Proceedings, IEEE INDIN 2008: 6th IEEE International Conference on Industrial Informatics : July 13-16, 2008, Daejeon Convention Center, Daejeon, Korea, Piscataway, NJ: IEEE Communications Society, 2008, p. 1160-1165Conference paper (Refereed)
    Abstract [en]

    Flexible manufacturing systems (FMS) and reconfigurable manufacturing systems (RMS) have both recently evolved to meet increasing demands for flexible manufacturing. This paper investigates the possibility of contact-less power and wireless data transfer to increase the flexibility and safety of various FMS modules by eliminating the need for power or data connections. The paper discusses advantages and implementation aspects of the proposed inductive power transfer (IPT) system and feasibility tests are undertaken to ensure the compatibility of IPT and the FMS modules, which form part of a lab-size modular test bed. In order to increase the cost effectiveness of the design, each module will run for an eight hour shift using a battery which is then automatically recharged via IPT. An energy aware custom switch mode charger has been designed and tested. A greedy heuristic (IEC 61499 compliant) scheduler is implemented to optimize the production schedule based on the level of charge. Design requirements for the charger, energy monitor and scheduler are discussed followed by performance results. The IPT system has been specified however it is still to be incorporated in to the final system

  • 37.
    Buzhinsky, Igor P.
    et al.
    Computer Technologies Laboratory, ITMO University, St.-Petersburg.
    Pang, Cheng
    Department of Electrical and Computer System Engineering, University of Auckland, University of Auckland, Department of Electrical and Computer Engineering.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Formal Modeling of Testing Software for Cyber-Physical Automation Systems2015In: IEEE TrustCom-BigDataSE-ISPA 2015: Helsinki, 20-22 Aug. 2015, Piscataway, NJ: IEEE Communications Society, 2015, p. 301-306, article id 7345664Conference paper (Refereed)
    Abstract [en]

    The paper presents a framework which uses formal models for testing control software for industrial automation systems. The formalism called Net Condition/Event Systems (NCES) is applied to model the program under test, along with the system under control (plant) and the testing environment. The benefits of using the framework include the opportunities to test systems with time delays without the need to wait, to test parameterized sets of systems with a single execution of a test suite, and to check test suites for correctness. The use of the framework is illustrated on a simple system consisting of a lab-scale plant and a control application for it

  • 38.
    Buzhinsky, Igor P.
    et al.
    Computer Technologies Laboratory, ITMO University, St.-Petersburg.
    Ulyantsev, Vladimir I.
    Computer Technologies Laboratory, ITMO University, St.-Petersburg.
    Veijalainen, Jari
    Computer Technologies Laboratory, ITMO University, St.-Petersburg.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Evolutionary approach to coverage testing of IEC 61499 function block applications2015In: IEEE 13th International Conference on Industrial Informatics (INDIN), 2015: Cambridge, United Kingdom, 22-24 July 2015, Piscataway, NJ: IEEE Communications Society, 2015, p. 1213-1218, article id 7281908Conference paper (Refereed)
    Abstract [en]

    The paper addresses the problem of coverage testing of industrial automation software represented in the IEC 61499 standard, one of the recent standards for distributed control system design. Contrary to model-based testing (MBT), the paper focuses on implementation coverage, not model coverage. An approach based on evolutionary algorithms is presented which generates coverage test suites for both basic and composite IEC 61499 function blocks. It employs two third-party tools, FBDK and EvoSuite. The evaluation of the approach was performed on a set of control applications for two lab-scale demonstration plants. Results show that the approach is applicable and shows good performance at least on basic function blocks. The generated tests suites helped to discover several unreachable system parts, which pinpointed errors in the systems under test

  • 39.
    Buzhinsky, Igor
    et al.
    Department of Electrical Engineering and Automation, Aalto University.
    Pakonen, Antti
    VTT Technical Research Centre of Finland, Espoo.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University.
    Explicit-state and symbolic model checking of nuclear I&C systems: A comparison2017In: Proceedings IECON 2017: 43rd Annual Conference of the IEEE Industrial Electronics Society, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 5439-5446Conference paper (Refereed)
    Abstract [en]

    In some fields of industrial automation, such as nuclear power plant (NPP) industry in Finland, thorough verification of systems and demonstration of their safety are mandatory. Model checking is one of the techniques to achieve a high level of reliability. The goal of this paper is practical: we explore which type of model checking - either explicit-state or symbolic - is more suitable to verify instrumentation and control (I&C) applications, represented as function block networks. Unlike previous studies, in addition to the common open-loop approach, which views the controller model alone, we consider closed-loop verification, where the plant is also modeled. In addition, we present a procedure to translate block networks to the language of the SPIN explicit-state model checker.

  • 40.
    Buzhinsky, Igor
    et al.
    Department of Electrical Engineering and Automation, Aalto University.
    Pakonen, Antti
    VTT Technical Research Centre of Finland, Espoo.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University.
    Scalable methods of discrete plant model generation for closed-loop model checking2017In: Proceedings IECON 2017: 43rd Annual Conference of the IEEE Industrial Electronics Society, Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 5483-5488Conference paper (Refereed)
    Abstract [en]

    To facilitate correctness and safety of mission-critical automation systems, formal methods should be applied in addition to simulation and testing. One of such formal methods is model checking, which is capable of verifying complex requirements for the system's model. If both the controller and the controlled plant are formally modeled, then the variant of this technique called closed-loop model checking can be applied. Recently, a technique of automatic plant model generation has been proposed which is applicable in this scenario. This paper continues the work in this direction by presenting two plant model construction approaches which are much more scalable with respect to the previous one, and puts this work into a more practical context. The approaches are evaluated on a case study from the nuclear automation domain

  • 41.
    Buzhinsky, Igor
    et al.
    Aalto University, Department of Electrical Engineering and Automation, Espoo, Finland; Computer Technology Department, ITMO University, St. Petersburg, Russian Federation.
    Pakonen, Antti
    VTT Technical Research Centre of Finland Ltd., Espoo, Finland.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Aalto University, Department of Electrical Engineering and Automation, Espoo, Finland.
    Synthesis-Aided Reliability Assurance of Basic Block Models for Model Checking Purposes2018In: Proceedings of the 2018 IEEE 27th International Symposium on Industrial Electronics (ISIE), IEEE, 2018, p. 669-674, article id 8433793Conference paper (Refereed)
    Abstract [en]

    In the Finnish nuclear industry, model checking, a formal verification technique, is used as an additional means of safety assurance for instrumentation and control (IC) system design. Since the code of vendor-specific basic function blocks used in IC is commonly closed, these blocks need to be modeled manually based on available specification. This modeling introduces an additional source of human factor into the verification process. To increase the reliability of the library of basic blocks used in nuclear IC verification, we apply formal synthesis techniques, which can construct finite-state models of reactive systems from behavior examples and temporal properties. Since these techniques have computational limitations and synthesized models are hard to understand even by an analyst, we do not use them in the final verification process. Instead, in an iterative process, behavioral differences between a synthesized model and a manual model implementation are identified and used to create a list of features of manual implementations which either violate the specification or show that the specification is ambiguous. 

  • 42.
    Buzhinsky, Igor
    et al.
    Department of Electrical Engineering and Automation, Aalto University.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Automatic Inference of Finite-State Plant Models from Traces and Temporal Properties2017In: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 13, no 4, p. 1521-1530, article id 7857798Article in journal (Refereed)
    Abstract [en]

    Closed-loop model checking, a formal verification technique for industrial automation systems, increases the richness of specifications to be checked and reduces the state space to be verified compared to the open-loop case. To be applied, it needs the controller and the plant formal models to be coupled. There are approaches for controller synthesis, but little has been done regarding plant model construction. While manual plant modeling is time consuming and error-prone, discretizing a simulation model of the plant leads to state excess. This paper aims to solve the problem of automatic plant model construction from existing specification, which is represented in the form of plant behavior examples, or traces, and temporal properties. The proposed method, which is based on the translation of the problem to the Boolean satisfiability problem, is evaluated and shown to be applicable on several case study plant model synthesis tasks and on randomly generated problem instances.

  • 43.
    Buzhinsky, Igor
    et al.
    Department of Electrical Engineering and Automation, Aalto University.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University.
    Modular Plant Model Synthesis from Behavior Traces and Temporal Properties2018In: IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Piscataway, Nj: Institute of Electrical and Electronics Engineers (IEEE), 2018, Vol. F134116Conference paper (Refereed)
    Abstract [en]

    Reliability of industrial automation software, which is usually ensured with testing and simulation, can be improved using formal analysis and, in particular, the technique of model checking. In model checking, considering the closed loop composition of the plant model and the controller model allows checking a larger class of properties than in the more traditional open-loop case, where the model of the controller is verified alone. Constructing the formal model of the plant automatically may significantly reduce human workload and mitigate the human factor issue. Commonly, complex industrial plants and controllers have modular structure, and thus the problem of automatic construction of a modular plant model is important. This paper proposes two techniques which extend an earlier proposed method of monolithic plant model construction to the modular case.

  • 44.
    Buzhinsky, Igor
    et al.
    Department of Electrical Engineering and Automation, Aalto University.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Plant model inference for closed-loop verification of control systems: Initial explorations2017In: IEEE International Conference on Industrial Informatics (INDIN), Piscataway, NJ: Institute of Electrical and Electronics Engineers (IEEE), 2017, p. 736-739, article id 7819256Conference paper (Refereed)
    Abstract [en]

    Closed-loop model checking, a formal verification technique for industrial automation systems, increases the richness of specifications to be checked and often helps to reduce size of the state space to be verified compared with the open-loop case. To be applied, it needs two components - the controller and the plant models - to be coupled. While there are approaches for obtaining controller models from implementation, specification or behavior examples, little has been done regarding automation of plant model construction. This paper aims to solve the problem of automatic plant model construction from existing specification, which is represented in the form of plant behavior examples and temporal properties

  • 45.
    Buzhinsky, Igor
    et al.
    Department of Electrical Engineering and Automation, Aalto University.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Department of Electrical Engineering and Automation, Aalto University.
    Testing Automation Systems by Means of Model Checking2018In: IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Piscataway, Nj: Institute of Electrical and Electronics Engineers (IEEE), 2018, Vol. F134116Conference paper (Refereed)
    Abstract [en]

    ndustrial automation systems are commonly obliged to comply with correctness requirements and safety standards. Testing and simulation are traditionally used to ensure this compliance. For mission-critical applications, formal verification and model checking in particular are also used, but such techniques are computationally intensive and difficult to apply in practice. This paper searches for synergies between testing and model checking by generalizing an earlier proposed formal test modeling framework. It presents a technique of testing automation systems with the use of model checking, which now supports multiple model checking environments and a more generic test case representation. The proposed technique is applied on a case study involving a simple safety-critical system with timing requirements. Experiments show that the technique is fast despite the use of formal methods and at the same time has several benefits compared to usual testing.

  • 46. Cai, Xiujun
    et al.
    Vyatkin, Valeriy
    Hanisch, Hans Michael
    Department of Engineering Sciences, Martin Luther University Halle-Wittenberg.
    Design and implementation of a prototype control system according to IEC 614992003In: ETFA 2003: 2003 IEEE Conference on Emerging Technologies and Factory Automation. Proceedings, Piscataway, NJ: IEEE Communications Society, 2003, p. 269-276Conference paper (Refereed)
  • 47.
    Cavadini, Franco A.
    et al.
    Synesis, SCARL, Via Cavour 2, 22074 Lomazzo, Italy.
    Montalbano, Giuseppe
    Synesis, SCARL, Via Cavour 2, 22074 Lomazzo, Italy.
    Kollegger, Gernot
    nxtControl, GmbH, Aumühlweg 3/B14, A-2544 Leobersdorf, Austria.
    Mayer, Horst
    nxtControl, GmbH, Aumühlweg 3/B14, A-2544 Leobersdorf, Austria.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    IEC-61499 Distributed Automation for the Next Generation of Manufacturing Systems2019In: The Digital Shopfloor: Industrial Automation in the Industry 4.0 Era Performance Analysis and Applications: Performance Analysis and Applications / [ed] John Soldatos; Oscar Lazaro; Franco Cavadini, River Publishers, 2019, p. 103-127Chapter in book (Other academic)
    Abstract [en]

    Global competition in the manufacturing sector is becoming fiercer and fiercer, with fast evolving requirements that must now take much more into account: rising product variety; product individualization; volatile markets; increasing relevance of value networks; shortening product life cycles. To fulfil these increasingly complex requirements, companies have to invest on new technological solutions and to focus the efforts on the conception of new automation platforms that could grant to the shopfloor systems the flexibility and re-configurability required to optimize their manufacturing processes, whether they are continuous, discrete or a combination of both. Daedalus is conceived to enable the full exploitation of the CPS’ virtualized intelligence concept, through the adoption of a completely distributed automation platform based on IEC-61499 standard, fostering the creation of a digital ecosystem that could go beyond the current limits of manufacturing control systems and propose an ever-growing market of innovative solutions for the design, engineering, production and maintenance of plants’ automation.

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  • 48.
    Chen, Yingxin
    et al.
    Shanghai Jiao Tong University, China. University of California Berkeley, US.
    Dai, Wenbin
    Shanghai Jiao Tong University, China.
    Zhang, Zhijie
    Shanghai Jiao Tong University, China.
    Pang, Cheng
    Jiangmen Goobotics Research Institute, Zhuxi Wisdom Valley, Jiangmen, China.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Aalto University, Finland.
    A Case Study on Knowledge Driven Code Generation for Software-Defined Industrial Cyber-Physical Systems2018In: Proceedings IECON 2018: 44th Annual Conference of the IEEE Industrial Electronics Society, IEEE, 2018, p. 4687-4692Conference paper (Refereed)
    Abstract [en]

    Industrial Cyber-Physical Systems (iCPS) enables coordination between various subsystems and devices based on real-time feedback data from sensors. iCPS must react rapidly to new requirements and adjust itself to fulfill new functionalities in no time. On the software side, control programs of iCPS need to be reconfigured dynamically. An efficient way for massive reconfiguration is automatic code generation. In this paper, a knowledge-driven code generation method is experimented for software-defined iCPS. Based on sensor values, actuators are controlled by the reasoning process with support of ontological knowledge base. The results demonstrate that iCPS could be driven by rules completely without programming control software.

  • 49.
    Cheng, Haibo
    et al.
    Shenyang Institute of Automation, Chinese Academy of Sciences,Lab. of Networked Control Systems,Shenyang,China.
    Han, Xiaoning
    Shenyang Institute of Automation, Chinese Academy of Sciences,Lab. of Networked Control Systems,Shenyang,China.
    Zeng, Peng
    Shenyang Institute of Automation, Chinese Academy of Sciences,Lab. of Networked Control Systems,Shenyang,China.
    Yu, Haibin
    Shenyang Institute of Automation, Chinese Academy of Sciences,Lab. of Networked Control Systems,Shenyang,China.
    Osipov, Evgeny
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science.
    ANN based Interwell Connectivity Analysis in Cyber-Physical Petroleum Systems2019In: Proceedings: 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), IEEE, 2019, p. 199-205Conference paper (Other academic)
    Abstract [en]

    In cyber-physical petroleum systems (CPPS), accurate estimation of interwell connectivity is an important process to know reservoir properties comprehensively, determine water injection rate scientifically, and enhance oil recovery effectively for oil and gas (O&G) field. In this study, an artificial neural network (ANN) based analysis method is proposed to estimate interwell connectivity. The generated neural network is used to define the mapping function between production wells and surrounding injection wells based on the historical water injection and liquid production data. Finally, the proposed method is applied to a synthetic reservoir model. Experimental results show that ANN based approach is an efficient method for analyzing interwell connectivity.

  • 50.
    Cheng, Haibo
    et al.
    Shenyang Institute of Automation, Chinese Academy of Sciences, State Key Laboratory of Robotics, Shenyang, China; Chinese Academy of Sciences, Key Laboratory of Networked Control Systems, Shenyang, China; Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China.
    He, Yunpeng
    Shenyang Institute of Automation, Chinese Academy of Sciences, State Key Laboratory of Robotics, Shenyang, China; Chinese Academy of Sciences, Key Laboratory of Networked Control Systems, Shenyang, China; Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China; University of Chinese Academy of Sciences, Beijing, China.
    Zeng, Peng
    Shenyang Institute of Automation, Chinese Academy of Sciences, State Key Laboratory of Robotics, Shenyang, China; Chinese Academy of Sciences, Key Laboratory of Networked Control Systems, Shenyang, China; Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China.
    Li, Shichao
    Shenyang Institute of Automation, Chinese Academy of Sciences, State Key Laboratory of Robotics, Shenyang, China; Chinese Academy of Sciences, Key Laboratory of Networked Control Systems, Shenyang, China; Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China.
    Vyatkin, Valeriy
    Luleå University of Technology, Department of Computer Science, Electrical and Space Engineering, Computer Science. Aalto University, Department of Electrical Engineering and Automation, Helsinki, Finland.
    Deep Learning-Based Prediction of Subsurface Oil Reservoir Pressure Using Spatio-Temporal Data2023In: IECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society, Institute of Electrical and Electronics Engineers (IEEE), 2023Conference paper (Refereed)
    Abstract [en]

    Prediction of subsurface oil reservoir pressure are critical to hydrocarbon production. However, the accurate pressure estimation faces great challenges due to the complexity and uncertainty of reservoir. The underground seepage flow and petrophysical parameters (permeability and porosity) are important but difficult to measure in oilfield. Deep learning methods have been successfully used in reservoir engineering and oil & gas production process. In this study, the effective but inaccessible subsurface seepage fields are not used, only the spatial coordinates and temporal information are selected as model input to predict reservoir pressure. A stacked GRU-based deep learning model is proposed to map the relationship between spatio-temporal data and reservoir pressure. The proposed deep learning method is verified by using a three-dimensional reservoir model, and compared with commonly-used methods. The results show that the stacked GRU model has a better performance and higher accuracy than other deep learning or machine learning methods in pressure prediction.

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