This book focuses on distributed and economic Model Predictive Control (MPC) with applications in different fields. MPC is one of the most successful advanced control methodologies due to the simplicity of the basic idea (measure the current state, predict and optimize the future behavior of the plant to determine an input signal, and repeat this procedure ad infinitum) and its capability to deal with constrained nonlinear multi-input multi-output systems. While the basic idea is simple, the rigorous analysis of the MPC closed loop can be quite involved. Here, distributed means that either the computation is distributed to meet real-time requirements for (very) large-scale systems or that distributed agents act autonomously while being coupled via the constraints and/or the control objective. In the latter case, communication is necessary to maintain feasibility or to recover system-wide optimal performance. The term economic refers to general control tasks and, thus, goes beyond the typically predominant control objective of set-point stabilization. Here, recently developed concepts like (strict) dissipativity of optimal control problems or turnpike properties play a crucial role. The book collects research and survey articles on recent ideas and it provides perspectives on current trends in nonlinear model predictive control. Indeed, the book is the outcome of a series of six workshops funded by the German Research Foundation (DFG) involving early-stage career scientists from different countries and from leading European industry stakeholders.

This book deals with several types of multi-dimensional control problems in the face of data uncertainty for vector cases-multi-dimensional multi-objective control problem with uncertain objective functionals, uncertain constraint functionals, and uncertain objective as well as constraint functionals, uncertain multi-dimensional multi-objective control problem with semi-infinite constraints, uncertain dual multi-dimensional multi-objective variational control problem, and second-order PDE&PDI constrained robust optimization problem. The book provides the solution approaches-an exact l1 penalty function approach, modified objective approach, robust approach-in the simplest way to solve the recent developing optimization problems in the sense of uncertainty.

This monograph explores applications of Carleman estimates in the study of stabilization and controllability properties of partial differential equations, including quantified unique continuation, logarithmic stabilization of the wave equation, and null-controllability of the heat equation. Where the first volume derived these estimates in regular open sets in Euclidean space and Dirichlet boundary conditions, here they are extended to Riemannian manifolds and more general boundary conditions. The book begins with the study of Lopatinskii-Sapiro boundary conditions for the Laplace-Beltrami operator, followed by derivation of Carleman estimates for this operator on Riemannian manifolds. Applications of Carleman estimates are explored next: quantified unique continuation issues, a proof of the logarithmic stabilization of the boundary-damped wave equation, and a spectral inequality with general boundary conditions to derive the null-controllability result for the heat equation. Two additional chapters consider some more advanced results on Carleman estimates. The final part of the book is devoted to exposition of some necessary background material: elements of differential and Riemannian geometry, and Sobolev spaces and Laplace problems on Riemannian manifolds.

The proliferation of Internet of Things (IoT) has enabled rapid enhancements for applications, not only in home and environment scenarios, but also in factory automation. Now, Industrial Internet of Things (IIoT) offers all the advantages of IoT to industry, with applications ranging from remote sensing and actuating, to de-centralization and autonomy. In this book, the editor presents the IIoT and its place during the new industrial revolution (Industry 4.0) as it takes us to a better, sustainable, automated, and safer world. The book covers the cross relations and implications of IIoT with existing wired/wireless communication/networking and safety technologies of the Industrial Networks. Moreover, the book includes practical use-case scenarios from the industry for the application of IIoT on smart factories, smart cities, and smart grids. IoT-driven advances in commercial and industrial building lighting and in street lighting are presented as an example to shed light on the application domain of IIoT. The state of the art in Industrial Automation is also presented to give a better understanding of the enabling technologies, potential advantages, and challenges of the Industry 4.0 and IIoT. Finally, yet importantly, the security section of the book covers the cyber-security related needs of the IIoT users and the services that might address these needs. User privacy, data ownership, and proprietary information handling related to IIoT networks are all investigated. Intrusion prevention, detection, and mitigation are all covered at the conclusion of the book.

This book covers some selected problems of the descriptor integer and fractional order positive continuous-time and discrete-time systems. The book consists of 3 chapters, 4 appendices and the list of references. Chapter 1 is devoted to descriptor integer order continuous-time and discrete-time linear systems. In Chapter 2, descriptor fractional order continuous-time and discrete-time linear systems are considered. Chapter 3 is devoted to the stability of descriptor continuous-time and discrete-time systems of integer and fractional orders. In Appendix A, extensions of the Cayley-Hamilton theorem for descriptor linear systems are given. Some methods for computation of the Drazin inverse are presented in Appendix B. In Appendix C, some basic definitions and theorems on Laplace transforms and Z-transforms are given. Some properties of the nilpotent matrices are given in Appendix D.

This thesis focuses on experimental studies on collective motion using swimming bacteria as model active-matter systems. It offers comprehensive reviews of state-of-the-art theories and experiments on collective motion from the viewpoint of nonequilibrium statistical physics. The author presents his experimental studies on two major classes of collective motion that had been well studied theoretically. Firstly, swimming filamentous bacteria in a thin fluid layer are shown to exhibit true, long-range orientational order and anomalously strong giant density fluctuations, which are considered universal and landmark signatures of collective motion by many numerical and theoretical works but have never been observed in real systems. Secondly, chaotic bacterial turbulence in a three-dimensional dense suspension without any long-range order as described in the first half is demonstrated to be capable of achieving antiferromagnetic vortex order by imposing a small number of constraints with appropriate periodicity. The experimental results presented significantly advance our fundamental understanding of order and fluctuations in collective motion of motile elements and their future applications.

RDF-based knowledge graphs require additional formalisms to be fully context-aware, which is presented in this book. This book also provides a collection of provenance techniques and state-of-the-art metadata-enhanced, provenance-aware, knowledge graph-based representations across multiple application domains, in order to demonstrate how to combine graph-based data models and provenance representations. This is important to make statements authoritative, verifiable, and reproducible, such as in biomedical, pharmaceutical, and cybersecurity applications, where the data source and generator can be just as important as the data itself. Capturing provenance is critical to ensure sound experimental results and rigorously designed research studies for patient and drug safety, pathology reports, and medical evidence generation. Similarly, provenance is needed for cyberthreat intelligence dashboards and attack maps that aggregate and/or fuse heterogeneous data from disparate data sources to differentiate between unimportant online events and dangerous cyberattacks, which is demonstrated in this book. Without provenance, data reliability and trustworthiness might be limited, causing data reuse, trust, reproducibility and accountability issues. This book primarily targets researchers who utilize knowledge graphs in their methods and approaches (this includes researchers from a variety of domains, such as cybersecurity, eHealth, data science, Semantic Web, etc.). This book collects core facts for the state of the art in provenance approaches and techniques, complemented by a critical review of existing approaches. New research directions are also provided that combine data science and knowledge graphs, for an increasingly important research topic.

The research presented in this book shows how combining deep neural networks with a special class of fuzzy logical rules and multi-criteria decision tools can make deep neural networks more interpretable - and even, in many cases, more efficient. Fuzzy logic together with multi-criteria decision-making tools provides very powerful tools for modeling human thinking. Based on their common theoretical basis, we propose a consistent framework for modeling human thinking by using the tools of all three fields: fuzzy logic, multi-criteria decision-making, and deep learning to help reduce the black-box nature of neural models; a challenge that is of vital importance to the whole research community.

This innovative monograph explores a new mathematical formalism in higher-order temporal logic for proving properties about the behavior of systems. Developed by the authors, the goal of this novel approach is to explain what occurs when multiple, distinct system components interact by using a category-theoretic description of behavior types based on sheaves. The authors demonstrate how to analyze the behaviors of elements in continuous and discrete dynamical systems so that each can be translated and compared to one another. Their temporal logic is also flexible enough that it can serve as a framework for other logics that work with similar models. The book begins with a discussion of behavior types, interval domains, and translation invariance, which serves as the groundwork for temporal type theory. From there, the authors lay out the logical preliminaries they need for their temporal modalities and explain the soundness of those logical semantics. These results are then applied to hybrid dynamical systems, differential equations, and labeled transition systems. A case study involving aircraft separation within the National Airspace System is provided to illustrate temporal type theory in action. Researchers in computer science, logic, and mathematics interested in topos-theoretic and category-theory-friendly approaches to system behavior will find this monograph to be an important resource. It can also serve as a supplemental text for a specialized graduate topics course.

The main theme of this book is recent progress in structure-preserving algorithms for solving initial value problems of oscillatory differential equations arising in a variety of research areas, such as astronomy, theoretical physics, electronics, quantum mechanics and engineering. It systematically describes the latest advances in the development of structure-preserving integrators for oscillatory differential equations, such as structure-preserving exponential integrators, functionally fitted energy-preserving integrators, exponential Fourier collocation methods, trigonometric collocation methods, and symmetric and arbitrarily high-order time-stepping methods. Most of the material presented here is drawn from the recent literature. Theoretical analysis of the newly developed schemes shows their advantages in the context of structure preservation. All the new methods introduced in this book are proven to be highly effective compared with the well-known codes in the scientific literature. This book also addresses challenging problems at the forefront of modern numerical analysis and presents a wide range of modern tools and techniques.

This book explores the genesis of ransomware and how the parallel emergence of encryption technologies has elevated ransomware to become the most prodigious cyber threat that enterprises are confronting. It also investigates the driving forces behind what has been dubbed the 'ransomware revolution' after a series of major attacks beginning in 2013, and how the advent of cryptocurrencies provided the catalyst for the development and increased profitability of ransomware, sparking a phenomenal rise in the number and complexity of ransomware attacks. This book analyzes why the speed of technology adoption has been a fundamental factor in the continued success of financially motivated cybercrime, and how the ease of public access to advanced encryption techniques has allowed malicious actors to continue to operate with increased anonymity across the internet. This anonymity has enabled increased collaboration between attackers, which has aided the development of new ransomware attacks, and led to an increasing level of technical complexity in ransomware attacks. This book highlights that the continuous expansion and early adoption of emerging technologies may be beyond the capacity of conventional risk managers and risk management frameworks. Researchers and advanced level students studying or working in computer science, business or criminology will find this book useful as a reference or secondary text. Professionals working in cybersecurity, cryptography, information technology, financial crime (and other related topics) will also welcome this book as a reference.

Design automation of electronic and hybrid systems is a steadily growing field of interest and a permanent challenge for researchers in Electronics, Computer Engineering and Computer Science. System Design Automation presents some recent results in design automation of different types of electronic and mechatronic systems. It deals with various topics of design automation, ranging from high level digital system synthesis, through analogue and heterogeneous system analysis and design, up to system modeling and simulation. Design automation is treated from the aspects of its theoretical fundamentals, its basic approach and its methods and tools. Several application cases are presented in detail. The book consists of three chapters: High-Level System Synthesis (Digital Hardware/Software Systems). Here embedded systems, distributed systems and processor arrays as well as hardware-software codesign are treated. Also three special application cases are discussed in detail; Analog and Heterogeneous System Design (System Approach and Methodology). This chapter copes with the analysis and design of hybrid systems comprised of analog and digital, electronic and mechanical components; System Simulation and Evaluation (Methods and Tools). In this chapter object-oriented Modelling, analog system simulation including fault-simulation, parameter optimization and system validation are regarded. The contents of the book are based on material presented at the Workshop System Design Automation (SDA 2000) organised by the Sonderforschungsbereich 358 of the Deutsche Forschungsgemeinschaft at TU Dresden.

This book extrapolates many of the concepts that are well defined for discrete-time deterministic sliding-mode control for use with discrete-time stochastic systems. It details sliding-function designs for various categories of linear time-invariant systems and its application for control. The resulting sliding-mode control addresses robustness issues and the functional-observer approach reduces the observer order substantially. Sliding-mode control (SMC) is designed for discrete-time stochastic systems, extended so that states lie within a specified band, and able to deal with incomplete information. Functional-observer-based SMC is designed for various clauses of stochastic systems: discrete-time; discrete-time with delay; state time-delayed; and those with parametric uncertainty. Stability considerations arising because of parametric uncertainty are taken into account and, where necessary, the effects of unmatched uncertainties mitigated. A simulation example is used to explain the use of the functional-observer approach to SMC design. Discrete-Time Stochastic Sliding-Mode Control Using Functional Observation will interest all researchers working in sliding-mode control and will be of particular assistance to graduate students in understanding the changes in design philosophy that arise when changing from continuous- to discrete-time systems. It helps to pave the way for further progress in applications of discrete-time SMC.

This book highlights research and survey articles dedicated to big data techniques for cyber-physical system (CPS), which addresses the close interactions and feedback controls between cyber components and physical components. The book first discusses some fundamental big data problems and solutions in large scale distributed CPSs. The book then addresses the design and control challenges in multiple CPS domains such as vehicular system, smart city, smart building, and digital microfluidic biochips. This book also presents the recent advances and trends in the maritime simulation system and the flood defence system.

This book presents novel results by participants of the conference "Control theory of infinite-dimensional systems" that took place in January 2018 at the FernUniversitat in Hagen. Topics include well-posedness, controllability, optimal control problems as well as stability of linear and nonlinear systems, and are covered by world-leading experts in these areas. A distinguishing feature of the contributions in this volume is the particular combination of researchers from different fields in mathematics working in an interdisciplinary fashion on joint projects in mathematical system theory. More explicitly, the fields of partial differential equations, semigroup theory, mathematical physics, graph and network theory as well as numerical analysis are all well-represented.

In the present book, the starting line is defined by a morphogenetic perspective on human communication and culture. The focus is on visual communication, music, religion (myth), and language, i.e., on the "symbolic forms" at the heart of human cultures (Ernst Cassirer). The term "morphogenesis" has more precisely the meaning given by Rene Thom (1923-2002) in his book "Morphogenesis and Structural Stability" (1972) and the notions of "self-organization" and cooperation of subsystems in the "Synergetics" of Hermann Haken (1927- ). The naturalization of communication and cultural phenomena is the favored strategy, but the major results of the involved disciplines (art history, music theory, religious science, and linguistics) are respected. Visual art from the Paleolithic to modernity stands for visual communication. The present book focuses on studies of classical painting and sculpture (e.g., Leonardo da Vinci, William Turner, and Henry Moore) and modern art (e.g., Jackson Pollock and Joseph Beuys). Musical morphogenesis embraces classical music (from J. S. Bach to Arnold Schoenberg) and political songwriting (Bob Dylan, Leonhard Cohen). The myths of pre-literary societies show the effects of self-organization in the re-assembly (bricolage) of traditions. Classical polytheistic and monotheistic religions demonstrate the unfolding of basic germs (religious attractors) and their reduction in periods of crisis, the self-organization of complex religious networks, and rationalized macro-structures (in theologies). Significant tendencies are analyzed in the case of Buddhism and Christianism. Eventually, a holistic view of symbolic communication and human culture emerges based on state- of- the- art in evolutionary biology, cognitive science, linguistics, and semiotics (philosophy of symbolic forms).

This monograph introduces breakthrough control algorithms for partial differential equation models with moving boundaries, the study of which is known as the Stefan problem. The algorithms can be used to improve the performance of various processes with phase changes, such as additive manufacturing. Using the authors' innovative design solutions, readers will also be equipped to apply estimation algorithms for real-world phase change dynamics, from polar ice to lithium-ion batteries. A historical treatment of the Stefan problem opens the book, situating readers in the larger context of the area. Following this, the chapters are organized into two parts. The first presents the design method and analysis of the boundary control and estimation algorithms. Part two then explores a number of applications, such as 3D printing via screw extrusion and laser sintering, and also discusses the experimental verifications conducted. A number of open problems and provided as well, offering readers multiple paths to explore in future research. Materials Phase Change PDE Control & Estimation is ideal for researchers and graduate students working on control and dynamical systems, and particularly those studying partial differential equations and moving boundaries. It will also appeal to industrial engineers and graduate students in engineering who are interested in this area.

This book focuses on how the BOXES Methodology, which is based on the work of Donald Michie, is applied to ill-defined real-time control systems with minimal a priori knowledge of the system. The method is applied to a variety of systems including the familiar pole and cart. This second edition includes a new section that covers some further observations and thoughts, problems, and evolutionary extensions that the reader will find useful in their own implementation of the method. This second edition includes a new section on how to handle jittering about a system boundary which in turn causes replicated run times to become part of the learning mechanism. It also addresses the aging of data values using a forgetfulness factor that causes wrong values of merit to be calculated. Another question that is addressed is "Should a BOXES cell ever be considered fully trained and, if so, excluded from further dynamic updates". Finally, it expands on how system boundaries may be shifted using data from many runs using an evolutionary paradigm.

This proceedings book presents state-of-the-art developments in theory, methodology, and applications of network analysis across sociology, computational science, education research, literature studies, political science, international relations, social media research, and urban studies. The papers comprising this collection were presented at the Fifth 'Networks in the Global World' conference organized by the Centre for German and European Studies of St. Petersburg University and Bielefeld University and held on July 7-9, 2020. This biannual conference series revolves around key interdisciplinary issues in the focus of network analysts, such as the multidimensional approach to social reality, translation of theories and methods across disciplines, and mixing of data and methods. The distinctive features of this book are the emphasis on in-depth linkages between theory, method, and applications, the blend of qualitative and quantitative methods, and the joint consideration of different network levels, types, and contexts. The topics covered by the papers include interrelation of social and cultural structures, constellations of power, and patterns of interaction in areas ranging from various types of communities (local, international, educational, political, and so on) to social media and literature. The book is useful for practicing researchers, graduate and postgraduate students, and educators interested in network analysis of social relations, politics, economy, and culture. Features that set the book apart from others in the field: * The book offers a unique cross-disciplinary blend of computational and ethnographic network analyses applied to a diverse spectrum of spheres, from literature and education to urban planning and policymaking. * Embracing conceptual, methodological, and empirical works, the book is among the few in network analysis to emphasize connections between theory, method, and applications. * The book brings together authors and empirical contexts from all over the globe, with a particular emphasis on European societies.

Following the emergence of quantum computing, the subsequent quantum revolution will be that of interconnecting individual quantum computers at the global level. In the same way that classical computers only realised their full potential with the emergence of the internet, a fully-realised quantum internet is the next stage of evolution for quantum computation. This cutting-edge book examines in detail how the quantum internet would evolve in practise, focusing not only on the technology itself, but also the implications it will have economically and politically, with numerous non-technical sections throughout the text providing broader context to the discussion. The book begins with a description of classical networks before introducing the key concepts behind quantum networks, such as quantum internet protocols, quantum cryptography, and cloud quantum computing. Written in an engaging style and accessible to graduate students in physics, engineering, computer science and mathematics.

"Fault-Tolerant Process Control" focuses on the development of general, yet practical, methods for the design of advanced fault-tolerant control systems; these ensure an efficient fault detection and a timely response to enhance fault recovery, prevent faults from propagating or developing into total failures, and reduce the risk of safety hazards. To this end, methods are presented for the design of advanced fault-tolerant control systems for chemical processes which explicitly deal with actuator/controller failures and sensor faults and data losses. Specifically, the book puts forward:

.A framework for detection, isolation and diagnosis of actuator and sensor faults for nonlinear systems;

. Controller reconfiguration and safe-parking-based fault-handling methodologies;

. Integrated-data- and model-based fault-detection and isolation and fault-tolerant control methods;

. Methods for handling sensor faults and data losses; and

. Methods for monitoring the performance of low-level PID loops.

The methodologies proposed employ nonlinear systems analysis, Lyapunov techniques, optimization, statistical methods and hybrid systems theory and are predicated upon the idea of integrating fault-detection, local feedback control, and supervisory control. The applicability and performance of the methods are demonstrated through a number of chemical process examples. "Fault-Tolerant Process Control" is a valuable resource for academic researchers, industrial practitioners as well as graduate students pursuing research in this area."

This volume constitutes the refereed and revised post-conference proceedings of the 5th IFIP WG 5.15 International Conference on Information Technology in Disaster Risk Reduction, ITDRR 2020, in Sofia, Bulgaria, in December 2020.* The 18 full papers and 6 short papers presented were carefully reviewed and selected from 52 submissions. The papers focus on various aspects and challenges of coping with disaster risk reduction. The main topics include areas such as natural disasters, remote sensing, big data, cloud computing, Internet of Things, mobile computing, emergency management, disaster information processing, disaster risk assessment and management. *The conference was held virtually.

This book offers a systematic and rigorous treatment of continuous-time Markov decision processes, covering both theory and possible applications to queueing systems, epidemiology, finance, and other fields. Unlike most books on the subject, much attention is paid to problems with functional constraints and the realizability of strategies. Three major methods of investigations are presented, based on dynamic programming, linear programming, and reduction to discrete-time problems. Although the main focus is on models with total (discounted or undiscounted) cost criteria, models with average cost criteria and with impulsive controls are also discussed in depth. The book is self-contained. A separate chapter is devoted to Markov pure jump processes and the appendices collect the requisite background on real analysis and applied probability. All the statements in the main text are proved in detail. Researchers and graduate students in applied probability, operational research, statistics and engineering will find this monograph interesting, useful and valuable.

This book highlights new trends and challenges in intelligent systems, which play an important part in the digital transformation of many areas of science and practice. It includes papers offering a deeper understanding of the human-centred perspective on artificial intelligence, of intelligent value co-creation, ethics, value-oriented digital models, transparency, and intelligent digital architectures and engineering to support digital services and intelligent systems, the transformation of structures in digital businesses and intelligent systems based on human practices, as well as the study of interaction and the co-adaptation of humans and systems. All papers were originally presented at the International KES Conference on Human Centred Intelligent Systems 2020 (KES HCIS 2020), held on June 17-19, 2020, in Split, Croatia.

Iterative Learning Control (ILC) differs from most existing control methods in the sense that, it exploits every possibility to incorporate past control informa tion, such as tracking errors and control input signals, into the construction of the present control action. There are two phases in Iterative Learning Control: first the long term memory components are used to store past control infor mation, then the stored control information is fused in a certain manner so as to ensure that the system meets control specifications such as convergence, robustness, etc. It is worth pointing out that, those control specifications may not be easily satisfied by other control methods as they require more prior knowledge of the process in the stage of the controller design. ILC requires much less information of the system variations to yield the desired dynamic be haviors. Due to its simplicity and effectiveness, ILC has received considerable attention and applications in many areas for the past one and half decades. Most contributions have been focused on developing new ILC algorithms with property analysis. Since 1992, the research in ILC has progressed by leaps and bounds. On one hand, substantial work has been conducted and reported in the core area of developing and analyzing new ILC algorithms. On the other hand, researchers have realized that integration of ILC with other control techniques may give rise to better controllers that exhibit desired performance which is impossible by any individual approach."