Analyzing Early Requirements of Cyber-physical Systems through Structure and Goal Modeling

Cyber-physical systems (CPS) integrate computation with physical processes. For the last years, CPS have been in the focus of research and are getting adopted in multiple domains like health care, automotive and smart factories. The use of CPS promises dynamic adaption of systems to changing environmental and economic conditions through autonomous CPS decisions based on the physical process. In industrial process automation, research and adoption of CPS have to account for the severe safety restrictions that dominate the system design in this domain. To transfer the benefits of CPS application to process automation, the CPS must be able to formally verify the safety of its autonomous reconfiguration decisions. This paper proposes a domain model for safety-critical CPS in industrial process automation to serve as foundation for formal CPS algorithms.

Dynamic behavior analysis is the area of investigation in the product lifecycle management (PLM) system. Behavioral modeling approach of a system is used to define dynamic behavior of a system. There is a big list of modeling approaches proposed by the researchers of various disciplines to simplify the analysis of system so that it is used as standard for system development in the real world. The cyber-physical system (CPS) is the next generation of system where the physical system acts smartly with the power of computing. Therefore, modeling of CPS is gaining popularity in the industrial design. This paper starts with the discussion of behavioral modeling era of a system and CPS respectively. Then, the survey of the state of the art of system behavioral modeling and CPS behavioral modeling is provided in which most of the approaches are reviewed PLM system. The system modeling survey is conducted based on the work done in the late 20th century to the recent years of 21st century. The CPS modeling survey is conducted based on the work done in the recent years of 21th century as this technology and modeling approach is emerging. Based on the discussion and survey, conclusion and future work will be explained.

Cyber-Physical System (CPS) involves the combination of physical processes with computation and communication systems. The recent advancements made in cloud computing, Wireless Sensor Network (WSN), healthcare sensors, etc. tend to develop CPS as a proficient model for healthcare applications especially, home patient care. Though several techniques have been proposed earlier related to CPS structures, only a handful of studies has focused on the design of CPS models for health care sector. So, the proposal for a dedicated CPS model for healthcare sector necessitates a significant interest to ensure data privacy. To overcome the challenges, the current research paper designs a Deep Learning-based Intrusion Detection and Image Classification for Secure CPS (DLIDIC-SCPS) model for healthcare sector. The aim of the proposed DLIDIC-SCPS model is to achieve secure image transmission and image classification process for CPS in healthcare sector. Primarily, data acquisition takes place with the help of sensors and detection of intrusions is performed using Fuzzy Deep Neural Network (FDNN) technique. Besides, Multiple Share Creation (MSC) approach is used to create several shares of medical image so as to accomplish security. Also, blockchain is employed as a distributed data storage entity to create a ledger that provides access to the client. For image classification, Inception v3 with Fuzzy Wavelet Neural Network (FWNN) is utilized that diagnose the disease from the applied medical image. Finally, Salp Swarm Algorithm (SSA) is utilized to fine tune the parameters involved in WNN model, thereby boosting its classification performance. A wide range of simulations was carried out to highlight the superiority of the proposed DLIDIC-SCPS technique. The simulation outcomes confirm that DLIDIC-SCPS approach demonstrates promising results in terms of security, privacy, and image classification outcomes over recent state-of-the-art techniques.

Security and Privacy Aspect of Cyber Physical Systems

Automation and the digital transformation have become important factors in the energy sector, as modern energy systems increasingly rely on communication and information technology to combine smart controls with hardware infrastructure. With the emergence of cyber-physical systems (CPS) as a trans-disciplinary field, such modern energy systems can be classified as cyber-physical energy systems (CPES), integrating the related research and development within a broader scope. An important aspect of the research and development related to CPS is to bridge the gap between the traditional engineering domains and computer science. This is especially true for CPES, where the related engineering domains have in the past come up with proven and reliable methods for designing even large and complex systems. However, existing modeling and simulation tools still struggle to cover all aspects of CPES. Hence, a combination of universal modeling languages and established, domain-specific tools (such as grid simulators and telecommunication simulators) is necessary. New methods, tools and algorithms are needed that are compact, computationally inexpensive, potentially self-organizing and intrinsically stable if applied to real energy systems.

Cyber-Physical Systems (CPS) integrates computing and physical processing: their behaviour is dictated by both computation and physical components. In this paper, we present a Model Checking approach for the automatic verification of the correctness of the system at hand. The strengths of our approach are the followings. First, we have implemented the CPS using the modelling and simulation based software JModelica to exploit its modular and parametrizables components. Second, we have verified the system's properties with a model-checking technique to exploit the automaticity of this approach and the completeness of the exploration of all the states of the CPS. In fact, with very few basic notions of the field to investigate, it is possible to design a complete model of a CPS. The system we model, for our proof of concept, is a Distributed Maximum Power Point Tracking (DMPPT) for photovoltaic systems, which relies on a control software to manage the system in every condition imposed by the environment (e.g. irradiation, temperature). We have parameterized the main physical inputs to carry out an automatic verification of a thorough simulation of the circuit under a large number of operational conditions, to deeply investigate the critical aspects of the system. The final goal of our study has been to design a tool to enable automatic verification using a model-checking approach in order to ensure the system correctness with respect to given requirements provided by the designer.

Middleware-based Cyber-Physical Production System Modeling for Operators

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Smart grids are electric grids that utilize advanced technologies of monitoring, control, and communication to supply reliable and secure energy, improve the efficiency of the system, and provide flexibility to the prosumers. The beginning of the smart grid era and the development in modern infrastructures of metering, communication, and energy storage have revolutionized the power grid. Smart grids are developed with complex physical networks and cyber systems thus enabling smart grids for the Internet of Energy (IoE). IoE is the cloud where sources of power generation and loads of power consumption are embedded with intelligence. Modern electric power grids are integrated with sensors used to provide measurements. The sensor measurements and the complex applications of various sensors cause a need for Cyber-Physical System (CPS). CPS is a class of systems that integrates physical process, computation, and networking. The CPS model of the smart grid helps in modeling and simulation for evaluation of the system performance and characteristics. The CPS model of the smart grid must enable the smart grid to be robust, 2allow future extensions, and compatible with web service technologies. The power generation sources and loads such as smart buildings are the physical layers, the sensors used for measurements form the cyber-physical integration and the data storage and processing using IOE forms the cyber layer of the smart grid. The CPS model of the smart grid helps in the integration of intelligent devices and allied information and communication technologies for robust and reliable operation in smart grids. In the smart grid paradigm, the energy management system has a vital role to increase the efficiency and reliability of the system. This chapter presents a CPS model for smart grid and the challenges associated with the development of the CPS model. In addition, this chapter describes the energy management system model of the smart grid.

The strategic application domains of Cyber Physical Systems (CPS) [7,6] include health care, transportation, managing large-scale physical infrastructures, and defense systems (avionics). In all these applications there is a need to acquire reliable resources in order to provide trustworthy services at every service request context. Hence we view CPS as a large distributed highway for services and supply chain management. In traditional service-oriented systems service, but not resource, is a first class entity in the architecture model and resources are assumed to be available at run time to provide services. However resource quality and availability are determining factors for timeliness and trustworthiness of CPS services, especially during emergencies. So in the service-oriented view of CPS discussed in this paper we place services around resources, because resource constrain service quality. We investigate a resource-centric, and context-dependent model for service-oriented CPS and discuss 3-tiered architecture for service-oriented CPS in this paper.

Rail transit is a typical Cyber-physical Systems (CPS). The study of urban rail transit CPS was carried out with the introduction of CPS into the urban rail transit system. Based on the analysis of CPS, the fundamental architecture of urban rail transit CPS was designed and the functions of corresponding layers were explained. The system model of urban rail transit CPS was proposed. The functions of the model and the interaction between each model were explained. The issue of heterogeneous networks integration in rail transit system and train system was analyzed. Meanwhile, according to the actual demand of security monitoring and management of train running, network controller between WSN and control bus was designed and verified. The results show that the network controller can well achieve data exchange between WSN and train network.

Currently, at NASA significant attention is paid to the development of an initiative on simulating and studying cyber-physical systems (CPS) (Cyber-Physical Systems Modeling and Analysis (CPSMA) Initiative, https://www.nasa.gov/centers/ames/cct/office/studies/cyber-physical_systems.html). CPS are a new class of physical systems describing the complex models of the behavior of spacecrafts equipped with high-performance software complexes of control and navigation (DRAFT Modeling, Simulation, Information Technology & Processing Roadmap Technology Area 11, https://www.nasa.gov/pdf/501321main_TA11-MSITP-DRAFT-Nov2010-A1.pdf). CPS could therefore be characterized as both hybrid systems combining software and hardware and mechatronic complexes containing electronic and mechanic components. In particular, when implementing space missions, CPS include systems for transforming coordinates and algorithms of spatial navigation referencing that have competitive advantages in the accuracy of parameters, the stability of the interaction between various components of CPS, and the possibility of adaptation to the change in dynamic behavior (DRAFT Robotics, Tele-Robotics and Autonomous Systems Roadmap Technology Area 04, https://www.nasa.gov/pdf/501622main_TA04-Robotics-DRAFT-Nov2010-A.pdf). The creation of simulation models for space navigation that could be used further in CPS is an important and relevant task. This chapter considers the development of the navigation simulation model for the lunar space satellite (LSS) referencing the dynamic reference selenocentric system on the basis of coordinates transformation using the regression modeling. The transformation process includes the generation of a photogrammetrically corrected image and referencing the observed lunar objects to the ones included in the digital maps of the Moon. By the coordinate position of an object observed by the LSS and using the software developed by the authors one calculates and compares altimetry parameters of the given point in relation to known selenocentric reference objects.

The challenges associated with developing accurate models for cyber-physical systems are attributable to the intrinsic concurrent and heterogeneous computations of these systems. Even though reasoning based on interconnected domain specific ontologies shows promise in enhancing modularity and joint functionality modelling, it has become necessary to build interoperable cyber-physical systems due to the growing pervasiveness of these systems. In this paper, we propose a semantically oriented distributed reasoning architecture for cyber-physical systems. This model accomplishes reasoning through a combination of heterogeneous models of computation. Using the flexibility of semantic agents as a formal representation for heterogeneous computational platforms, we define autonomous and intelligent agent-based reasoning procedure for distributed cyber-physical systems. Sensor networks underpin the semantic capabilities of this architecture, and semantic reasoning based on Markov logic networks is adopted to address uncertainty in modelling. To illustrate feasibility of this approach, we present a Markov logic based semantic event model for cyber-physical systems and discuss a case study of event handling and processing in a smart home.

Construction of approximate reasoning model for dynamic CPS network and system parameter identification

Cyber Physical Systems (CPS) are redefining modern engineering practices by bringing the computational systems together with physical processes, boosting efficiency, security, and sustainability in different industries. This research highlights the influence of CPS in different sectors: its power to facilitate realtime decision making, predictive maintenance, and cybersecurity issues. The context in which this study occurs is to the application of digital twin technology in CPS — which is physical systems’ simulation for performance optimization and downtime reduction. The research includes the analysis of the efficiency of cybersecurity measures applied in CPS environment, the identification of vulnerabilities, and the suggestions of solutions for the mitigation of a cyber threat. Digital twins and predictive maintenance appears to improve the system performance by 30%, reduces the downtime by 25% due to application. Moreover, the research addresses upcoming concerns of sustainable practices in CPS and emerging technologies such as Industry 4.0 that promote resource optimization and waste reduction. The results show that CPS can improve both the operational efficiency and the environmental sustainability by enabling a smarter resource management. This work advances our understanding of trends, challenges and future directions in CPS as a means to inform engineering management practices, which are enabled by CPS.