Cyber-Physical Systems

Summary

Cyber Physical Systems (CPS) interface the physical environment, human environment together with the information world. CPS enable the physical world to merge with the virtual leading to an Internet of things, data and services. One example of CPS is an intelligent manufacturing line, where the machine can perform many work processes by communicating with the components. Sensor virtualization plays a major roles when it comes to applications of cyber physical systems. So far there were no commercial systems for manufacturing using sensor virtualisation for CPS. These have been at present at prototyping and research stage mainly in education and healthcare fields. The European Union is already investing around 300 Million Euro per year for 10 years to pursue “world leadership” through advanced strategic research and technology development related to  CPS (include 170 Million Euro per year in public funds and 130 Million Euro per year in private funds. Cyber-Physical Systems Laboratory (CPSL) at Washington University in St. Louis performs cutting-edge research on real-time systems, wireless sensor networks, embedded systems and cyber-physical systems that cross-cut computing, networking and other engineering disciplines. Cyber-physical systems are rapidly becoming critical to the business success of many companies and the mission success of many government agencies. In transportation (intelligent vehicles and traffic control, intelligent structures and pavements), manufacturing (smart production equipment, processes, automation, control, and networks; new product design), telecommunications, consumer electronics, and health and medical equipment (body area networks and assistive systems), and intelligent infrastructure (smart utility grids and smart buildings/ structures) the value share of electronics, computing, communications, sensing, and actuation is expected to exceed 50% of the cost by the end of the decade. One of the major issues for CPS application is reliability, safety and security. For CPS to be reliable, safe, and secure, systems must be able to adapt to the physical environment and withstand both cyber and physical attacks while maintaining data integrity and robustness.

The barriers for market applicability of CPS are:

  • Lack of metrics and tools for CPS verification and validation.
  • Modelling fidelity: Inability to apply formal methods at appropriate abstraction levels
  • System integration and compositionality: Interoperating various modules and unifying standards from different domains and sectors.

Relation to CREMA

One central aspect to process manufacturing data is an interface between the hardware sensors and software components. Due to the high amount of various sensors from different manufacturing assets delivering heterogeneous data, the challenge will be to abstract the sensors and to virtualise it for other CREMA components. This component shall process the data, which is delivered by the manufacturing assets in a harmonised way. Users request data invisibly from the Cloud-based RAID Infrastructure and the Big Data, Knowledge and Analytics component in order to view it on the CREMA Dashboard. CPS allows sensor data from manufacturing assets to be accessible by the user. In terms of this data, the user is able to react and interact. To solve this issue, it is needed to take the following steps:

  • Cyber-Physical Systems (CPS): Enables a communication between Sensors and CREMA
  • Sensor Abstraction: Defines common grounds of the amount of various sensors
  • Virtualisation: Represents sensors in the CREMA system

The CPS has to be integrated to access the sensor sources to process the data in a standardised way. A data gateway will be implemented which marshals the data of the sensor sources to a format that can be used within CREMA. Where applicable, these will use existing approaches to standardise access to various heterogeneous sensor data, e.g. as recommended by the W3C Semantic Sensor Network Incubator Group. The data can then be accessed directly or via the Big Data, Knowledge and Analytics component or the Cloud-based RAID Infrastructure. In the field of manufacturing, there are many different sensors, which measure various data. One task is to analyse the common grounds of the various sensors, categorise and unify them, and to build an appropriate sensor abstraction layer. After the sensor abstraction is completed, the sensor sources are ready for virtualisation. Virtualisation is responsible for representing the sensor source in CREMA and allows the user’s processes to have control over the sensor. By providing a CPS and sensor abstraction and interoperability framework, CREMA allows the envisioned end-to-end integration of ICT systems across the complete supply chain. CPS will also be interfaced as actors in order to control the manufacturing process. This allows influencing and actively controlling real-world manufacturing processes and therefore adapting them if necessary.

General References

Cyber-Physical Systems Laboratory (CPSL) at Washington University in St. Louis http://www.wustl.edu/

Articles

  1. A.A. Nazarenko, and L.M. Camarinha-Matos, "Towards collaborative Cyber-Physical Systems." Proc. IEEE International Young Engineers Forum (YEF-ECE), 2017
    The concept of Cyber-Physical Systems (CPS) is the next stage of Embedded Systems development and involves tied integration of physical, cyber, and communication components. The rapid growth in number of interconnected devices and objects requires new governance, aggregation and structuring mechanisms for objects themselves and data generated by them. Furthermore, new organizational structures are needed to cope with scalability and integration of new devices/objects without disturbing already functioning devices/objects. As objects become smarter, with increasing computational capabilities, the implementation of collaboration mechanisms among them becomes relevant. This paper discusses current trends and challenges for implementation of collaborative CPS. Moreover, a smart home scenario is presented, in order to illustrate such challenges
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  2. Giraldo, Jairo, et al., "Security and Privacy in Cyber-Physical Systems: A Survey of Surveys", IEEE Design & Test, 2017.
    Cyber-Physical Systems (CPS) are engineered systems combining computation, communications, and physical resources. Over the last decade—alongside technical advances in CPS—a vibrant and active community of security and privacy researchers have proposed and developed a mature research agenda addressing fundamental problems and risks of CPS deployments. The field has matured to a point where there are now several CPS security surveys. In this paper we highlight the diversity of research presenting by a meta-survey of CPS security and privacy surveys. Our goal is two-fold: first, we want to present newcomers to the field with an overview of the trends and main results in CPS security, and privacy; and secondly, we want to help established researchers in this field, identify other areas or domains where their cross-cutting principles can apply.
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  3. P. Fraga Lamas, "Enabling technologies and cyber-physical systems for mission-critical scenarios", 2017
    Reliable transport systems, defense, public safety and quality assurance in the Industry 4.0 are essential in a modern society. In a mission-critical scenario, a mission failure would jeopardize human lives and put at risk some other assets whose impairment or loss would significantly harm society or business results. Even small degradations of the communications supporting the mission could have large and possibly dire consequences. On the one hand, mission-critical organizations wish to utilize the most modern, disruptive and innovative communication systems and technologies, and yet, on the other hand, need to comply with strict requirements, which are very different to those of non critical scenarios. The aim of this thesis is to assess the feasibility of applying emerging technologies like Internet of Things (IoT), Cyber-Physical Systems (CPS) and 4G broadband communications in mission-critical scenarios along three key critical infrastructure sectors: transportation, defense and public safety, and shipbuilding. Regarding the transport sector, this thesis provides an understanding of the progress of communications technologies used for railways since the implantation of Global System for Mobile communications-Railways (GSM-R). The aim of this work is to envision the potential contribution of Long Term Evolution (LTE) to provide additional features that GSM-R would never support. Furthermore, the ability of Industrial IoT for revolutionizing the railway industry and confront today's challenges is presented. Moreover, a detailed review of the most common flaws found in Radio Frequency IDentification (RFID) based IoT systems is presented, including the latest attacks described in the literature. As a result, a novel methodology for auditing security and reverse engineering RFID communications in transport applications is introduced. The second sector selected is driven by new operational needs and the challenges that arise from modern military deployments. The strategic advantages of 4G broadband technologies massively deployed in civil scenarios are examined. Furthermore, this thesis analyzes the great potential for applying IoT technologies to revolutionize modern warfare and provide benefits similar to those in industry. It identifies scenarios where defense and public safety could leverage better commercial IoT capabilities to deliver greater survivability to the warfighter or first responders, while reducing costs and increasing operation efficiency and effectiveness. The last part is devoted to the shipbuilding industry. After defining the novel concept of Shipyard 4.0, how a shipyard pipe workshop works and what are the requirements for building a smart pipe system are described in detail. Furthermore, the foundations for enabling an affordable CPS for Shipyards 4.0 are presented. The CPS proposed consists of a network of beacons that continuously collect information about the location of the pipes. Its design allows shipyards to obtain more information on the pipes and to make better use of it. Moreover, it is indicated how to build a positioning system from scratch in an environment as harsh in terms of communications as a shipyard, showing an example of its architecture and implementation.
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  4. D. Kolberg, et al., "CyProF – Insights from a Framework for Designing Cyber-Physical Systems in Production Environments", In: Engelbert Westkämper; Thomas Bauernhansl (Hrsg.). Factories of the Future in the digital environment - Proceedings of the 49th CIRP Conference on Manufacturing Systems. CIRP Conference on Manufactoring Systems (CIRP CMS), located at CIRP Conference on Manufacturing Systems, May 25-27, Stuttgart, Germany, Elsevier, Amsterdam, 2017.
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  5. Lee, Edward Ashford, and Sanjit A. Seshia, "Introduction to embedded systems: A cyber-physical systems approach", MIT Press, 2016
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  6. J. Knight, J. Xiang, and K. Sullivan, "A Rigorous Definition of Cyber-Physical Systems", J Trustworthy Cyber-Physical Systems Engineering, 47, 2016.
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  7. Jazdi, Nasser, "Cyber physical systems in the context of Industry 4.0." Proc. IEEE International Conference on Automation, Quality and Testing, Robotics; IEEE, 2014.
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  8. J. Lee, B. Bagheri, and H-A. Kao, "Recent advances and trends of cyber-physical systems and big data analytics in industrial informatics", Proc. International Conference on Industrial Informatics (INDIN), 2014
    In today’s competitive business environment, companies are facing challenges in dealing with big data issues for rapid decision making for improved productivity. Many manufacturing systems are not ready to manage big data due to the lack of smart analytics tools. Germany is leading a transformation toward 4th Generation Industrial Revolution (Industry 4.0) based on Cyber-Physical System based manufacturing and service innovation. As more software and embedded intelligence are integrated in industrial products and systems, predictive technologies can further intertwine intelligent algorithms with electronics and tether-free intelligence to predict product performance degradation and autonomously manage and optimize product service needs. This article addresses the trends of industrial transformation in big data environment as well as the readiness of smart predictive informatics tools to manage big data to achieve transparency and productivity
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  9. J. Jensen et al., "Virtualizing Cyber-Physical Systems: Bringing CPS to Online Education," First Workshop on CPS Education (CPS-Ed), 2013.
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  10. Energetics Incorporated, Columbia, Maryland for the National Institute of Standards and Technology NIST, "Foundations for Innovation in Cyber-Physical Systems," Workshop Summary Report, Rosemont, Illinois, Mar. 2012.
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  11. Rajkumar, Ragunathan Raj, et al., "Cyber-physical systems: the next computing revolution", Proc. 47th Design Automation Conference, ACM, 2010.
    Cyber-physical systems (CPS) are physical and engineered systems whose operations are monitored, coordinated, controlled and integrated by a computing and communication core. Just as the internet transformed how humans interact with one another, cyber-physical systems will transform how we interact with the physical world around us. Many grand challenges await in the economically vital domains of transportation, health-care, manufacturing, agriculture, energy, defense, aerospace and buildings. The design, construction and verification of cyber-physical systems pose a multitude of technical challenges that must be addressed by a cross-disciplinary community of researchers and educators.
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  12. E.A. Lee, "Cyber physical systems: Design challenges", Proc. 11th IEEE International Symposium on Oriented Real-Time Distributed Object Computing (ISORC), IEEE, 2008.
    Cyber-Physical Systems (CPS) are integrations of computation and physical processes. Embedded computers and networks monitor and control the physical processes, usually with feedback loops where physical processes affect computations and vice versa. The economic and societal potential of such systems is vastly greater than what has been realized, and major investments are being made worldwide to develop the technology. There are considerable challenges, particularly because the physical components of such systems introduce safety and reliability requirements qualitatively different from those in general-purpose computing. Moreover, physical components are qualitatively different from object-oriented software components. Standard abstractions based on method calls and threads do not work. This paper examines the challenges in designing such systems, and in particular raises the question of whether today’s computing and networking technologies provide an adequate foundation for CPS. It concludes that it will not be sufficient to improve design processes, raise the level of abstraction, or verify (formally or otherwise) designs that are built on today’s abstractions. To realize the full potential of CPS, we will have to rebuild computing and networking abstractions. These abstractions will have to embrace physical dynamics and computation in a unified way.
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Software

No references have been entered yet.

Projects

  1. NSF Project "A Science of CPS Robustness" (2016 - 2019) Link
    Cyber-Physical Systems (CPS) offer the promise for radical changes to our everyday life by enabling the physical world to be programmed in the same way that a computer is programmed. The physical world, however, is far less predictable than a computer and this renders the design of CPS very challenging. In order to reduce the impact of unforeseen events arising from the physical world, or even from the cyber world, this project develops a science of CPS robustness. A robust CPS will only modestly deviate from its desired behavior upon the occurrence of unforeseen circumstances and has the ability to recover once these disrupting circumstances subside. The intellectual merit of this project is the development of a science of CPS robustness that harnesses the intricate interactions between cyber and physical components to obtain CPS that are able to operate in a wide range of unpredictable environments. The project?s broader significance and importance is the enablement of vast number of applications requiring CPS to operate seamlessly in unpredictable environments such as the internet-of-things or smart and connected communities. At the technical level, this project leverages existing notions of robustness for cyber systems, such as self-stabilizing algorithms, and for physical systems, such as input-to-state stability, to create a science of CPS robustness. Expected outcomes include new temporal logics to specify CPS robustness, verification and synthesis algorithms for CPS robustness, as well as compositional design flows.
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  2. CPS Frontiers NSF Project (2013-2018) Link
    This CPS Frontiers project addresses highly dynamic Cyber-Physical Systems (CPSs), understood as systems where a computing delay of a few milliseconds or an incorrectly computed response to a disturbance can lead to catastrophic consequences. Such is the case of cars losing traction when cornering at high speed, unmanned air vehicles performing critical maneuvers such as landing, or disaster and rescue response bipedal robots rushing through the rubble to collect information or save human lives. The preceding examples currently share a common element: the design of their control software is made possible by extensive experience, laborious testing and fine tuning of parameters, and yet, the resulting closed-loop system has no formal guarantees of meeting specifications.

    The vision of the project is to provide a methodology that allows for complex and dynamic CPSs to meet real-world requirements in an efficient and robust way through the formal synthesis of control software. The research is developing a formal framework for correct-by-construction control software synthesis for highly dynamic CPSs with broad applications to automotive safety systems, prostheses, exoskeletons, aerospace systems, manufacturing, and legged robotics.

    The design methodology developed here will improve the competitiveness of segments of industry that require a tight integration between hardware and highly advanced control software such as: automotive (dynamic stability and control), aerospace (UAVs), medical (prosthetics, orthotics, and exoskeleton design) and robotics (legged locomotion). To enhance the impact of these efforts, the PIs are developing interdisciplinary teaching materials to be made freely available and disseminating their work to a broad audience.
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  3. VISTRA EU FP7 Project (2011–2014) Link
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  4. NSF Project "Control of Distributed Cyber-Physical Systems under Partial Information and Limited Communication" (2009 - 2013) Link
    The principal objective of this project is the development of novel control architectures and computationally efficient controller design algorithms for distributed cyber-physical systems with decentralized information infrastructures and limited communication capabilities. We are interested in distributed cyber-physical systems where the system components are able to communicate with one another. Cooperative active safety in Intelligent Transportation Systems is our focus cyber-physical application. Our methodology for design of communicating distributed hybrid controllers aims to integrate in a novel manner discrete-event controller design and hybrid controller design and optimization. Both safety and liveness specifications will be addressed. The methodology to be developed exploits problem decomposition and is aimed at cyber-physical systems that share features of modularity in system representation, partial information, and limited communication. The technical approach consists of the following steps: (i) abstraction of the essential features of the cyber-physical system as a formal discrete-event model; (ii) synthesis of a set of distributed discrete-event control laws as well as sensor activation and communication strategies for the system agents; (iii) incorporation of the underlying continuous dynamics of the cyber-physical system with the preceding distributed control logic for the purpose of hybrid controller design and quantitative performance optimization; (iv) iteration between steps (ii) and (iii) for performance improvement.
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  5. SmartFactoryKL Link
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This page was last changed on 9 June 2017, at 16:30.


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