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This book provides a new perspective on modeling cyber-physical systems (CPS), using a data-driven approach. The authors cover the use of state-of-the-art machine learning and artificial intelligence algorithms for modeling various aspect of the CPS. This book provides insight on how a data-driven modeling approach can be utilized to take advantage of the relation between the cyber and the physical domain of the CPS to aid the first-principle approach in capturing the stochastic phenomena affecting the CPS. The authors provide practical use cases of the data-driven modeling approach for securing the CPS, presenting novel attack models, building and maintaining the digital twin of the physical system. The book also presents novel, data-driven algorithms to handle non- Euclidean data. In summary, this book presents a novel perspective for modeling the CPS.
This book highlights original approaches of modelling and intelligent control of cyber-physical systems covering both theoretical and practical aspects. The novel contribution of the book covers the transformation of scientific research and their results into applications for cyber-physical systems design and operation during the whole life cycle in different domains. Given its scope, the book offers an excellent reference book for researchers and other readers in the fields of cyber-physical systems modelling and intelligent control, space exploration and practical implementation of cyber-physical systems. The book also benefits researchers and practitioners in artificial intelligence and machine learning, as described results can be applied in cyber-physical systems design and cost-effectively maintenance. The target audience of this book also includes practitioners and experts, as well as state authorities and representatives of international organizations interested in creating mechanisms for implementing Cyber-Physical Systems projects. .
In this dissertation, we propose a cyber-physical system model, and based on this model, present algorithms for a set of distributed computing problems. Our model specifies a cyber-physical system as a combination of cyber-infrastructure, physical-infrastructure, and user behavior specification. The cyber-infrastructure is superimposed on the physical-infrastructure and continuously monitors its (physical-infrastructure's) changing state. Users operate in the physical-infrastructure and interact with the cyber-infrastructure using hand-held devices and sensors; and their behavior is specified in terms of actions they can perform (e.g., move, observe). While in traditional distributed systems, users interact solely via the underlying cyber-infrastructure, users in a cyber-physical system may interact directly with one another, access sensor data directly, and perform actions asynchronously with respect to the underlying cyber-infrastructure. These additional types of interactions have an impact on how distributed algorithms for cyber-physical systems are designed. We augment distributed mutual exclusion and predicate detection algorithms so that they can accommodate user behavior, interactions among them and the physical-infrastructure. The new algorithms have two components - one describing the behavior of the users in the physical-infrastructure and the other describing the algorithms in the cyber-infrastructure. Each combination of users' behavior and an algorithm in the cyber-infrastructure yields a different cyber-physical system algorithm. We have performed extensive simulation study of our algorithms using OMNeT++ simulation engine and Uppaal model checker. We also propose Cyber-Physical System Modeling Language (CPSML) to specify cyber-physical systems, and a centralized global state recording algorithm.
Model-based tools and methods are playing important roles in the design and analysis of cyber-physical systems before building and testing physical prototypes. The development of increasingly complex CPSs requires the use of multiple tools for different phases of the development lifecycle, which in turn depends on the ability of the supporting tools to interoperate. However, currently no vendor provides comprehensive end-to-end systems engineering tool support across the entire product lifecycle, and no mature solution currently exists for integrating different system modeling and simulation languages, tools and algorithms in the CPSs design process. Thus, modeling and simulation tools are still used separately in industry. The unique challenges in integration of CPSs are a result of the increasing heterogeneity of components and their interactions, increasing size of systems, and essential design requirements from various stakeholders. The corresponding system development involves several specialists in different domains, often using different modeling languages and tools. In order to address the challenges of CPSs and facilitate design of system architecture and design integration of different models, significant progress needs to be made towards model-based integration of multiple design tools, languages, and algorithms into a single integrated modeling and simulation environment. In this thesis we present the need for methods and tools with the aim of developing techniques for numerically stable co-simulation, advanced simulation model analysis, simulation-based optimization, and traceability capability, and making them more accessible to the model-based cyber physical product development process, leading to more efficient simulation. In particular, the contributions of this thesis are as follows: 1) development of a model-based dynamic optimization approach by integrating optimization into the model development process; 2) development of a graphical co-modeling editor and co-simulation framework for modeling, connecting, and unified system simulation of several different modeling tools using the TLM technique; 3) development of a tool-supported method for multidisciplinary collaborative modeling and traceability support throughout the development process for CPSs; 4) development of an advanced simulation modeling analysis tool for more efficient simulation.
CYBER-PHYSICAL DISTRIBUTED SYSTEMS Gather detailed knowledge and insights into cyber-physical systems behaviors from a cutting-edge reference written by leading voices in the field In Cyber-Physical Distributed Systems: Modeling, Reliability Analysis and Applications, distinguished researchers and authors Drs. Huadong Mo, Giovanni Sansavini, and Min Xie deliver a detailed exploration of the modeling and reliability analysis of cyber physical systems through applications in infrastructure and energy and power systems. The book focuses on the integrated modeling of systems that bring together physical and cyber elements and analyzing their stochastic behaviors and reliability with a view to controlling and managing them. The book offers a comprehensive treatment on the aging process and corresponding online maintenance, network degradation, and cyber-attacks occurring in cyber-physical systems. The authors include many illustrative examples and case studies based on real-world systems and offer readers a rich set of references for further research and study. Cyber-Physical Distributed Systems covers recent advances in combinatorial models and algorithms for cyber-physical systems modeling and analysis. The book also includes: A general introduction to traditional physical/cyber systems, and the challenges, research trends, and opportunities for real cyber-physical systems applications that general readers will find interesting and useful Discussions of general modeling, assessment, verification, and optimization of industrial cyber-physical systems Explorations of stability analysis and enhancement of cyber-physical systems, including the integration of physical systems and open communication networks A detailed treatment of a system-of-systems framework for the reliability analysis and optimal maintenance of distributed systems with aging components Perfect for undergraduate and graduate students in computer science, electrical engineering, cyber security, industrial and system engineering departments, Cyber-Physical Distributed Systems will also earn a place on the bookshelves of students taking courses related to reliability, risk and control engineering from a system perspective. Reliability, safety and industrial control professionals will also benefit greatly from this book.
This book is devoted to intelligent models and algorithms as the core components of cyber-physical systems. The complexity of cyber-physical systems developing and deploying requires new approaches to its modelling and design. Presents results in the field of modelling technologies that leverage the exploitation of artificial intelligence, including artificial general intelligence (AGI) and weak artificial intelligence. Provides scientific, practical, and methodological approaches based on bio-inspired methods, fuzzy models and algorithms, predictive modelling, computer vision and image processing. The target audience of the book are practitioners, enterprises representatives, scientists, PhD and Master students who perform scientific research or applications of intelligent models and algorithms in cyber-physical systems for various domains.
A foundational text that offers a rigorous introduction to the principles of design, specification, modeling, and analysis of cyber-physical systems. A cyber-physical system consists of a collection of computing devices communicating with one another and interacting with the physical world via sensors and actuators in a feedback loop. Increasingly, such systems are everywhere, from smart buildings to medical devices to automobiles. This textbook offers a rigorous and comprehensive introduction to the principles of design, specification, modeling, and analysis of cyber-physical systems. The book draws on a diverse set of subdisciplines, including model-based design, concurrency theory, distributed algorithms, formal methods of specification and verification, control theory, real-time systems, and hybrid systems, explaining the core ideas from each that are relevant to system design and analysis. The book explains how formal models provide mathematical abstractions to manage the complexity of a system design. It covers both synchronous and asynchronous models for concurrent computation, continuous-time models for dynamical systems, and hybrid systems for integrating discrete and continuous evolution. The role of correctness requirements in the design of reliable systems is illustrated with a range of specification formalisms and the associated techniques for formal verification. The topics include safety and liveness requirements, temporal logic, model checking, deductive verification, stability analysis of linear systems, and real-time scheduling algorithms. Principles of modeling, specification, and analysis are illustrated by constructing solutions to representative design problems from distributed algorithms, network protocols, control design, and robotics. This book provides the rapidly expanding field of cyber-physical systems with a long-needed foundational text by an established authority. It is suitable for classroom use or as a reference for professionals.
Offers a one-stop reference on the application of advanced modeling and simulation (M&S) in cyber physical systems (CPS) engineering This book provides the state-of-the-art in methods and technologies that aim to elaborate on the modeling and simulation support to cyber physical systems (CPS) engineering across many sectors such as healthcare, smart grid, or smart home. It presents a compilation of simulation-based methods, technologies, and approaches that encourage the reader to incorporate simulation technologies in their CPS engineering endeavors, supporting management of complexity challenges in such endeavors. Complexity Challenges in Cyber Physical Systems: Using Modeling and Simulation (M&S) to Support Intelligence, Adaptation and Autonomy is laid out in four sections. The first section provides an overview of complexities associated with the application of M&S to CPS Engineering. It discusses M&S in the context of autonomous systems involvement within the North Atlantic Treaty Organization (NATO). The second section provides a more detailed description of the challenges in applying modeling to the operation, risk and design of holistic CPS. The third section delves in details of simulation support to CPS engineering followed by the engineering practices to incorporate the cyber element to build resilient CPS sociotechnical systems. Finally, the fourth section presents a research agenda for handling complexity in application of M&S for CPS engineering. In addition, this text: Introduces a unifying framework for hierarchical co-simulations of cyber physical systems (CPS) Provides understanding of the cycle of macro-level behavior dynamically arising from spaciotemporal interactions between parts at the micro-level Describes a simulation platform for characterizing resilience of CPS Complexity Challenges in Cyber Physical Systems has been written for researchers, practitioners, lecturers, and graduate students in computer engineering who want to learn all about M&S support to addressing complexity in CPS and its applications in today’s and tomorrow’s world.
This book constitutes the proceedings of the 6th International Workshopon Design, Modeling, and Evaluation of Cyber Physical Systems, CyPhy2016, held in conjunction with ESWeek 2016, in Pittsburgh, PA, USA, inOctober 2016. The 9 papers presented in this volume were carefully reviewed and selected from 14 submissions. They broadly interpret, from a diverse set of disciplines, the modeling, simulation, and evaluation of cyber-physical systems with a particular focus on techniques and components to enable and support virtual prototyping and testing.
Cyber-physical systems (CPSs) combine cyber capabilities, such as computation or communication, with physical capabilities, such as motion or other physical processes. Cars, aircraft, and robots are prime examples, because they move physically in space in a way that is determined by discrete computerized control algorithms. Designing these algorithms is challenging due to their tight coupling with physical behavior, while it is vital that these algorithms be correct because we rely on them for safety-critical tasks. This textbook teaches undergraduate students the core principles behind CPSs. It shows them how to develop models and controls; identify safety specifications and critical properties; reason rigorously about CPS models; leverage multi-dynamical systems compositionality to tame CPS complexity; identify required control constraints; verify CPS models of appropriate scale in logic; and develop an intuition for operational effects. The book is supported with homework exercises, lecture videos, and slides.