This book describes a user-friendly, evolutionary algorithms-based framework for estimating data-driven models for a wide class of dynamical systems, including linear and nonlinear ones. The methodology addresses the problem of automating the process of estimating data-driven models from a user's perspective. By combining elementary building blocks, it learns the dynamic relations governing the system from data, giving model estimates with various trade-offs, e.g. between complexity and accuracy. The evaluation of the method on a set of academic, benchmark and real-word problems is reported in detail. Overall, the book offers a state-of-the-art review on the problem of nonlinear model estimation and automated model selection for dynamical systems, reporting on a significant scientific advance that will pave the way to increasing automation in system identification.

New finite elements are needed as well in research as in industry environments for thedevelopment of virtual prediction techniques. The design and implementation of novel finiteelements for specific purposes is a tedious and time consuming task, especially for nonlinearformulations. The automation of this process can help to speed up this processconsiderably since the generation of the final computer code can be accelerated by order ofseveral magnitudes.This book provides the reader with the required knowledge needed to employ modernautomatic tools like AceGen within solid mechanics in a successful way. It covers the rangefrom the theoretical background, algorithmic treatments to many different applications. Thebook is written for advanced students in the engineering field and for researchers ineducational and industrial environments.

A survey of current knowledge about Hamiltonian systems with three or more degrees of freedom and related topics. The Hamiltonian systems appearing in most of the applications are non-integrable. Hence methods to prove non-integrability results are presented and the different meaning attributed to non-integrability are discussed. For systems near an integrable one, it can be shown that, under suitable conditions, some parts of the integrable structure, most of the invariant tori, survive. Many of the papers discuss near-integrable systems. From a topological point of view, some singularities must appear in different problems, either caustics, geodesics, moving wavefronts, etc. This is also related to singularities in the projections of invariant objects, and can be used as a signature of these objects. Hyperbolic dynamics appear as a source on unpredictable behaviour and several mechanisms of hyperbolicity are presented. The destruction of tori leads to Aubrey-Mather objects, and this is touched on for a related class of systems. Examples without periodic orbits are constructed, against a classical conjecture. Other topics concern higher dimensional systems, either finite (networks and localised vibrations on them) or infinite, like the quasiperiodic SchrAdinger operator or nonlinear hyperbolic PDE displaying quasiperiodic solutions. Most of the applications presented concern celestial mechanics problems, like the asteroid problem, the design of spacecraft orbits, and methods to compute periodic solutions.

This book presents emerging work in the co-evolving fields of design-led systemics, referred to as systemic design to distinguish it from the engineering and hard science epistemologies of system design or systems engineering. There are significant societal forces and organizational demands impelling the requirement for "better means of change" through integrated design practices of systems and services. Here we call on advanced design to lead programs of strategic scale and higher complexity (e.g., social policy, healthcare, education, urbanization) while adapting systems thinking methods, creatively pushing the boundaries beyond the popular modes of systems dynamics and soft systems. Systemic design is distinguished by its scale, social complexity and integration - it is concerned with higher-order systems that that entail multiple subsystems. By integrating systems thinking and its methods, systemic design brings human-centred design to complex, multi-stakeholder service systems. As designers engage with ever more complex problem areas, it is necessary to draw on a basis other than individual creativity and contemporary "design thinking" methods. Systems theories can co-evolve with a new school of design theory to resolve informed action on today's highly resilient complex problems and can deal effectively with demanding, contested and high-stakes challenges.

This book focuses on modern technologies and systems for solving problems in the energy sector. It is shown that bioenergy is one of the promising areas of energy development. The book collected the experience of scientists from many countries in the research of renewable energy. The advantages of renewable energy are general availability, renewability, environmental friendliness. The analysis carried out by the authors shows the current state of renewable energy in the world, its trends and prospects. New measuring systems are presented, which can become the basis for measuring the thermal characteristics of various types of fuels, including biofuels, insulating materials, enclosing structures, etc. System for monitoring of grainy biomass comminution with the use of genetic algorithms has been presented and described. New technologies for the construction of power plants based on renewable energy sources have been proposed and investigated.

In this volume, author Tim Gorichanaz seeks to re-frame the discussion of information engagement through the lens of information experience, an exciting emerging area within information science. Unlike traditional information behavior research, which is limited to how people need, seek, and search for information, information experience looks at how people understand, use, and are shaped by information. In this way, information experience connects with other human-centered areas of information research and design, including information literacy and human-computer interaction. Split into three parts, Information Experience in Theory and Design presents a multifaceted investigation of information experience, centered around the themes of understanding, self, and meaning. Part One (Understanding) explores the link between information, understanding and questioning; how moral change arises from information; and how to design for understanding. Part Two (Self) explores the concept of the human self as information; the links between information, identity and society; and how to design for self-care. Finally, Part Three (Meaning) explores the connection between information and meaning; how meaning and craft contribute to the good life; and how to design for meaning. Offering a rigorous theoretical foundation for information experience and insights for design, Gorichanaz brings together research from across the information field as well as philosophy. For researchers or students in any area of the information field, from librarianship to human-computer interaction, this is an exciting new text investigating a fascinating new field of study.

This book introduces iterative learning control (ILC) and its applications to the new equations such as fractional order equations, impulsive equations, delay equations, and multi-agent systems, which have not been presented in other books on conventional fields. ILC is an important branch of intelligent control, which is applicable to robotics, process control, and biological systems. The fractional version of ILC updating laws and formation control are presented in this book. ILC design for impulsive equations and inclusions are also established. The broad variety of achieved results with rigorous proofs and many numerical examples make this book unique. This book is useful for graduate students studying ILC involving fractional derivatives and impulsive conditions as well as for researchers working in pure and applied mathematics, physics, mechanics, engineering, biology, and related disciplines.

This book explores the universe and its subsystems from the three lenses of evolutionary (contingent), developmental (predictable), and complex (adaptive) processes at all scales. It draws from prolific experts within the academic disciplines of complexity science, physical science, information and computer science, theoretical and evo-devo biology, cosmology, astrobiology, evolutionary theory, developmental theory, and philosophy. The chapters come from a Satellite Meeting, "Evolution, Development and Complexity" (EDC) hosted at the Conference on Complex Systems, in Cancun, 2017. The contributions have been peer-reviewed and contributors from outside the conference were invited to submit chapters to ensure full coverage of the topics. This book explores many issues within the field of EDC such as the interaction of evolutionary stochasticity and developmental determinism in biological systems and what they might teach us about these twin processes in other complex systems. This text will appeal to students and researchers within the complex systems and EDC fields.

This book investigates the disagreement behavior analysis problems for signed networks in the presence of both cooperative and antagonistic interactions among agents. Owing to the existing antagonistic interactions, signed networks exhibit a variety of disagreement behaviors subject to different topology conditions, especially in comparison with commonly considered unsigned networks involving only cooperative interactions among agents. Since signed networks are generally adopted to describe the dynamics of some practical network systems, they have attracted much attention in many areas, such as biology, sociology, economics, and politics. By focusing on agents with the first-order linear dynamics, the book establishes the systematic behavior analysis frameworks for signed networks, under which diverse disagreement behaviors have been disclosed, including both convergence and fluctuation behaviors, regardless of static or dynamic network topologies. In particular, a class of dynamic signed networks has been introduced, together with the associated dynamic distributed controller design and disagreement behavior analysis of agents. This book is intended for undergraduate and graduate students, engineers, and researchers who are interested in control of network systems, multi-agent systems, social networks, and so on.

The production and consumption of information and communication technologies (or ICTs) are becoming deeply embedded within our societies. The influence and implications of this have an impact at a macro level, in the way our governments, economies, and businesses operate, andat a micro level in our everyday lives. This handbook is about the many challenges presented by ICTs. It sets out an intellectual agenda that examines the implications of ICTs for individuals, organizations, democracy, and the economy. Explicity interdisciplinary, and combining empirical research with theoretical work, it is organised around four themes covering the knowledge economy; organizational dynamics, strategy, and design; governance and democracy; and culture, community and new media literacies. It provides a comprehensive resource for those working in the social sciences, and in the physical sciences and engineering fields, with leading contemporary research informed principally by the disciplines of anthropology, economics, philosophy, politics, and sociology.

This new 4th edition offers an introduction to optimal control theory and its diverse applications in management science and economics. It introduces students to the concept of the maximum principle in continuous (as well as discrete) time by combining dynamic programming and Kuhn-Tucker theory. While some mathematical background is needed, the emphasis of the book is not on mathematical rigor, but on modeling realistic situations encountered in business and economics. It applies optimal control theory to the functional areas of management including finance, production and marketing, as well as the economics of growth and of natural resources. In addition, it features material on stochastic Nash and Stackelberg differential games and an adverse selection model in the principal-agent framework. Exercises are included in each chapter, while the answers to selected exercises help deepen readers' understanding of the material covered. Also included are appendices of supplementary material on the solution of differential equations, the calculus of variations and its ties to the maximum principle, and special topics including the Kalman filter, certainty equivalence, singular control, a global saddle point theorem, Sethi-Skiba points, and distributed parameter systems. Optimal control methods are used to determine optimal ways to control a dynamic system. The theoretical work in this field serves as the foundation for the book, in which the author applies it to business management problems developed from his own research and classroom instruction. The new edition has been refined and updated, making it a valuable resource for graduate courses on applied optimal control theory, but also for financial and industrial engineers, economists, and operational researchers interested in applying dynamic optimization in their fields.

An exposition of the interplay between the modelling of dynamic systems and the design of feedback controllers based on these models is the main goal of this book. The combination of both subjects into a cohesive development allows the consistent treatment of both problems to yield powerful new tools for the improvement of system performance. Central among the themes of this work is the observation that operation of a system in feedback with a controller exposes the areas in which the model fit is constraining the controller performance achieved. The book presents new techniques for the understanding of the iterative improvement of performance through the successive fitting of models using closed-loop data and the design of high-performance controllers using these models. The subject matter includes: New approaches to understanding how to affect the fit of dynamical models to physical processes through the choice of experiments, data pre-filtering and model structure; connections between robust control design methods and their dependency on the quality of model fit; experimental design in which data collected in operation under feedback can reveal areas that limit the performance achieved; iterative approaches to link these model-fitting and control design phases in a cogent manner so as to achieve improved performance overall. The authors of individual chapters are some of the most renowned and authoritative figures in the fields of system identification and control design.

Conti examines presidential rhetoric on trade, providing a detailed analysis of presidential trade arguments and strategies throughout American history. She then concentrates on the rhetoric of contemporary presidents, who have had to contend with both the burgeoning trade deficit and the displacement of military competitiveness with post-cold war economic competitiveness. Despite vast disparities in governing philosophies and strategies, Presidents Reagan, Bush, and Clinton all preached the virtues of free trade while continuing a policy of select protectionist actions. As Conti suggests, the arcane details of trade policy, the continuing pervasiveness of nontariff barriers, and the impending negotiation of international trade agreements combine to make presidential leadership on economic issues critical. How effective that leadership can be is, in large part, dependent upon the effectiveness of presidential rhetoric. Students, scholars, and researchers in the field of speech communication and rhetoric, political communication, public affairs, and the presidency will find this a stimulating survey.

Photonics has long been considered an attractive substrate for next generation implementations of machine-learning concepts. Reservoir Computing tremendously facilitated the realization of recurrent neural networks in analogue hardware. This concept exploits the properties of complex nonlinear dynamical systems, giving rise to photonic reservoirs implemented by semiconductor lasers, telecommunication modulators and integrated photonic chips.

This book contains all refereed papers that were accepted to the seventh edition of the international conference " Complex Systems Design & Management Paris" (CSD&M Paris 2016) which took place in Paris (France) on the December 13-14, 2016 These proceedings cover the most recent trends in the emerging field of complex systems sciences & practices from an industrial and academic perspective, including the main industrial domains (aeronautic & aerospace, defense & security, electronics & robotics, energy & environment, healthcare & welfare services, software & e-services, transportation), scientific & technical topics (systems fundamentals, systems architecture & engineering, systems metrics & quality, system is modeling tools) and system types (artificial ecosystems, embedded systems, software & information systems, systems of systems, transportation systems). The CSD&M Paris 2016 conference is organized under the guidance of the CESAMES non-profit organization, address: CESAMES, 8 rue de Hanovre, 75002 Paris, France.

This book focuses on a central question in the field of complex systems: Given a fluctuating (in time or space), uni- or multi-variant sequentially measured set of experimental data (even noisy data), how should one analyse non-parametrically the data, assess underlying trends, uncover characteristics of the fluctuations (including diffusion and jump contributions), and construct a stochastic evolution equation? Here, the term "non-parametrically" exemplifies that all the functions and parameters of the constructed stochastic evolution equation can be determined directly from the measured data. The book provides an overview of methods that have been developed for the analysis of fluctuating time series and of spatially disordered structures. Thanks to its feasibility and simplicity, it has been successfully applied to fluctuating time series and spatially disordered structures of complex systems studied in scientific fields such as physics, astrophysics, meteorology, earth science, engineering, finance, medicine and the neurosciences, and has led to a number of important results. The book also includes the numerical and analytical approaches to the analyses of complex time series that are most common in the physical and natural sciences. Further, it is self-contained and readily accessible to students, scientists, and researchers who are familiar with traditional methods of mathematics, such as ordinary, and partial differential equations. The codes for analysing continuous time series are available in an R package developed by the research group Turbulence, Wind energy and Stochastic (TWiSt) at the Carl von Ossietzky University of Oldenburg under the supervision of Prof. Dr. Joachim Peinke. This package makes it possible to extract the (stochastic) evolution equation underlying a set of data or measurements.

This book aims to bring together the latest innovative knowledge, analysis, and synthesis of fractional control problems of nonlinear systems as well as some related applications. Fractional order systems (FOS) are dynamical systems that can be modelled by a fractional differential equation carried with a non-integer derivative. In the last few decades, the growth of science and engineering systems has considerably stimulated the employment of fractional calculus in many subjects of control theory, for example, in stability, stabilization, controllability, observability, observer design, and fault estimation. The application of control theory in FOS is an important issue in many engineering applications. So, to accurately describe these systems, the fractional order differential equations have been introduced.

At present, concerning intensive development of computer hardware and software, computer-based methods for modeling of difficult problems have become the main technique for theoretical and applied investigations. Many unsolved tasks for evolutionary systems (ES) are an important class of such problems. ES relate to economic systems on the whole and separate branches and businesses, scientific and art centers, ecological systems, populations, separate species of animals and plants, human organisms, different subsystems of organisms, cells of animals and plants, and soon. Available methods for modeling of complex systems have received considerable attention and led to significant results. No large-scale programs are done without methods of modeling today. Power programs, health programs, cosmos investigations, economy designs, etc. are a few examples of such programs. Nevertheless, in connection with the permanent complication of contemporary problems, existing means are in need of subsequent renovation and perfection. In the monograph, along with analysis of contemporary means, new classes of mathematical models (MM) which can be used for modeling in the most difficult cases are proposed and justified. The main peculiarities of these MM offer possibilities for the description ofES; creation and restoration processes; dynamics of elimination or reservation of obsolete technology in ES; dynamics of resources distribution for fulfillment of internal and external functions ofES; and so on. The complexity of the problems allows us to refer to the theory and applications of these MM as the mathematical theory of development. For simplicity, the title "Model Development and Optimization" was adopted.

This book is in honor of Yasuhiko Takahara, a first-class researcher who has been active for some 50 years at the global level in systems research. Researchers and practitioners from Japan and other countries who have been influenced by Takahara have come together from far and wide to contribute their major research masterpieces in the field of systems research in the broadest sense. While the roots of Takahara's systems research are in general systems theory and systems control theory, he developed his research and teaching in diverse directions such as management information science, engineering, social simulation, and systems thinking. As a result, many of the researchers and practitioners he supervised or influenced have established their own positions and are now active around the world in a wide range of systems research. Volume I is a collection of their masterpieces or representative works in the field of systems theory and modeling.

This book develops a dynamical model of the orbital motion of Lorentz spacecraft in both unperturbed and J2-perturbed environments. It explicitly discusses three kinds of typical space missions involving relative orbital control: spacecraft hovering, rendezvous, and formation flying. Subsequently, it puts forward designs for both open-loop and closed-loop control schemes propelled or augmented by the geomagnetic Lorentz force. These control schemes are entirely novel and represent a significantly departure from previous approaches.

This thesis reports on novel methods for gain-scheduling and fault tolerant control (FTC). It begins by analyzing the connection between the linear parameter varying (LPV) and Takagi-Sugeno (TS) paradigms. This is then followed by a detailed description of the design of robust and shifting state-feedback controllers for these systems. Furthermore, it presents two approaches to fault-tolerant control: the first is based on a robust polytopic controller design, while the second involves a reconfiguration of the reference model and the addition of virtual actuators into the loop. Inaddition the thesis offers a thorough review of the state-of-the art in gain scheduling and fault-tolerant control, with a special emphasis on LPV and TS systems.

This book presents recent advances in control and filter design for Takagi-Sugeno (T-S) fuzzy systems with switched parameters. Thanks to its powerful ability in transforming complicated nonlinear systems into a set of linear subsystems, the T-S fuzzy model has received considerable attention from those the field of control science and engineering. Typical applications of T-S fuzzy systems include communication networks, and mechanical and power electronics systems. Practical systems often experience abrupt variations in their parameters or structures due to outside disturbances or component failures, and random switching mechanisms have been used to model these stochastic changes, such as the Markov jump principle. There are three general types of controller/filter for fuzzy Markov jump systems: mode-independent, mode-dependent and asynchronous. Mode-independence does not focus on whether modes are accessible and ignores partially useful mode information, which results in some conservatism. The mode-dependent design approach relies on timely, complete and correct information regarding the mode of the studied plant. Factors like component failures and data dropouts often make it difficult to obtain exact mode messages, which further make the mode-dependent controllers/filters less useful. Recently, to overcome these issues, researchers have focused on asynchronous techniques. Asynchronous modes are accessed by observing the original systems based on certain probabilities. The book investigates the problems associated with controller/filter design for all three types. It also considers various networked constraints, such as data dropouts and time delays, and analyzes the performances of the systems based on Lyapunov function and matrix inequality techniques, including the stochastic stability, dissipativity, and $H_\infty$. The book not only shows how these approaches solve the control and filtering problems effectively, but also offers potential meaningful research directions and ideas. Covering a variety of fields, including continuous-time and discrete-time Markov processes, fuzzy systems, robust control, and filter design problems, the book is primarily intended for researchers in system and control theory, and is also a valuable reference resource for graduate and undergraduate students. Further, it provides cases of fuzzy control problems that are of interest to scientists, engineers and researchers in the field of intelligent control. Lastly it is useful for advanced courses focusing on fuzzy modeling, analysis, and control.

This book reports on the development and assessment of a novel framework for studying neural interactions (the connectome) and their dynamics (the chronnectome). Using EEG recordings taken during an auditory oddball task performed by 48 patients with schizophrenia and 87 healthy controls, and applying local and network measures, changes in brain activation from pre-stimulus to cognitive response were assessed, and significant differences were observed between the patients and controls. This book investigates the source of the network abnormalities and presents new evidence for the disconnection hypothesis and the aberrant salience hypothesis with regard to schizophrenia. Moreover, it puts forward a novel approach to combining local regularity measures and graph measures in order to characterize schizophrenia brain dynamics, and presents interesting findings on the regularity of brain patterns in healthy control subjects versus patients with schizophrenia. Besides providing new evidence for the disconnection hypothesis, it offers a source of inspiration for future research directions in the field.

The present volume, published at the occasion of his 100th birthday anniversary, is a collection of articles that reviews the impact of Kolomogorov's work in the physical sciences and provides an introduction to the modern developments that have been triggered in this way to encompass recent applications in biology, chemistry, information sciences and finance.