Autonomous manipulation is a challenge in robotic technologies. It refers to the capability of a mobile robot system with one or more manipulators that performs intervention tasks requiring physical contacts in unstructured environments and without continuous human supervision. Achieving autonomous manipulation capability is a quantum leap in robotic technologies as it is currently beyond the state of the art in robotics.

This book addresses issues with the complexity of the problems encountered in autonomous manipulation including representation and modeling of robotic structures, kinematic and dynamic robotic control, kinematic and algorithmic singularity avoidance, dynamic task priority, workspace optimization and environment perception. Further development in autonomous manipulation should be able to provide robust improvements of the solutions for all of the above issues. The book provides an extensive tract on sensory-based autonomous manipulation for intervention tasks in unstructured environments. After presenting the theoretical foundations for kinematic and dynamic modelling as well as task-priority based kinematic control of multi-body systems, the work is focused on one of the most advanced underwater vehicle-manipulator system, SAUVIM (Semi-Autonomous Underwater Vehicle for Intervention Missions). Solutions to the problem of target identification and localization are proposed, a number of significant case studies are discussed and practical examples and experimental/simulation results are presented. The book may inspire the robot research community to further investigate critical issues in autonomous manipulation and to develop robot systems that can profoundly impact our society for the better."

This monograph presents new model-based design methods for trajectory planning, feedback stabilization, state estimation, and tracking control of distributed-parameter systems governed by partial differential equations (PDEs). Flatness and backstepping techniques and their generalization to PDEs with higher-dimensional spatial domain lie at the core of this treatise. This includes the development of systematic late lumping design procedures and the deduction of semi-numerical approaches using suitable approximation methods. Theoretical developments are combined with both simulation examples and experimental results to bridge the gap between mathematical theory and control engineering practice in the rapidly evolving PDE control area. The text is divided into five parts featuring: - a literature survey of paradigms and control design methods for PDE systems - the first principle mathematical modeling of applications arising in heat and mass transfer, interconnected multi-agent systems, and piezo-actuated smart elastic structures - the generalization of flatness-based trajectory planning and feedforward control to parabolic and biharmonic PDE systems defined on general higher-dimensional domains - an extension of the backstepping approach to the feedback control and observer design for parabolic PDEs with parallelepiped domain and spatially and time varying parameters - the development of design techniques to realize exponentially stabilizing tracking control - the evaluation in simulations and experiments Control of Higher-Dimensional PDEs - Flatness and Backstepping Designs is an advanced research monograph for graduate students in applied mathematics, control theory, and related fields. The book may serve as a reference to recent developments for researchers and control engineers interested in the analysis and control of systems governed by PDEs.

This book, dedicated to Professor Georgi M. Dimirovski on his anniversary, contains new research directions, challenges, and many relevant applications related to many aspects within the broadly perceived areas of systems and control, including signal analysis and intelligent systems. The project comprises two volumes with papers written by well known and very active researchers and practitioners. The first volume is focused on more foundational aspects related to general issues in systems science and mathematical systems, various problems in control and automation, and the use of computational and artificial intelligence in the context of systems modeling and control. The second volume is concerned with a presentation of relevant applications, notably in robotics, computer networks, telecommunication, fault detection/diagnosis, as well as in biology and medicine, and economic, financial, and social systems too.

Autonomy Oriented Computing is a comprehensive reference for scientists, engineers, and other professionals concerned with this promising development in computer science. It can also be used as a text in graduate/undergraduate programs in a broad range of computer-related disciplines, including Robotics and Automation, Amorphous Computing, Image Processing, Programming Paradigms, Computational Biology, etc.

Part One describes the basic concepts and characteristics of an AOC system and enumerates the critical design and engineering issues faced in AOC system development. Part Two gives detailed analyses of methodologies and case studies to evaluate AOC used in problem solving and complex system modeling. The final chapter outlines possibilities for future research and development.

Numerous illustrative examples, experimental case studies, and exercises at the end of each chapter of Autonomy Oriented Computing help particularize and consolidate the methodologies and theories presented.

Characterized by its multi-level interdisciplinary character, communication has become a variable field -- one in which the level of analysis varies. This has had important ramifications for the study of communication because, to some extent, the questions one asks are determined by the methods one has available to answer them. As a result, communication research is characterized by the plethora of both qualitative and quantitative approaches used by its practitioners. These include survey and experimental methods, and content, historical, and rhetorical analyses.
A variety of tools has been developed in cognitive psychology and psychophysiology which attempts to measure "thinking" without asking people how they do it. This book is devoted to exploring how these methods might be used to further knowledge about the process of communication. The methods chosen have all been used extensively in cognitive and experimental psychology. Each chapter in this book is designed to describe the history of the method being introduced, the theory behind it, how to go about using it, and how it has already been used to study some area of communication. The methods introduced here vary widely in terms of the amount of equipment and training needed to use them. Some require only theoretical knowledge and a paper and pencil; others require more elaborate hardware and software for implementation. These methods also vary widely in terms of what sorts of variables they can be used to measure. Some of them adapt quite readily to traditional communication variables like persuasion, attitude change, and knowledge; others are more applicable to process type variables such as attention, arousal, involvement, encoding, and retrieval.

This book presents unique compendium of groundbreaking ideas where scientists from many different backgrounds are united in their interest in interdisciplinary approaches towards origins and development of cancers, innovative ways of searching for cancer treatment and the role of cancer in the evolution. Chapters give an unequivocal slice of all areas that relate to a quest for understanding cancer and its origin as many-fold nonlinear system, complexity of the cancer developments, a search for cancer treatment using artificial intelligence and evolutionary optimisation, novel modelling techniques, molecular origin of cancer, the role of cancer in evolution of species, interpretation of cancer in terms of artificial life and artificial immune systems, swarm intelligence, cellular automata, computational systems biology, genetic networks, cellular computing, validation through in vitro/vivo tumour models and tumour on chip devices. The book is an inspiring blend of theoretical and experimental results, concepts and paradigms. Distinctive features The book advances widely popular topics of cancer origin, treatment and understanding of its progress The book is comprised of unique chapters written by world top experts in theoretical and applied oncology, complexity theory, mathematics, computer science. The book illustrates attractive examples of mathematical and computer models and experimental setups.

This book offers a complete and detailed introduction to the theory of discrete dynamical systems, with special attention to stability of fixed points and periodic orbits. It provides a solid mathematical background and the essential basic knowledge for further developments such as, for instance, deterministic chaos theory, for which many other references are available (but sometimes, without an exhaustive presentation of preliminary notions). Readers will find a discussion of topics sometimes neglected in the research literature, such as a comparison between different predictions achievable by the discrete time model and the continuous time model of the same application. Another novel aspect of this book is an accurate analysis of the way a fixed point may lose stability, introducing and comparing several notions of instability: simple instability, repulsivity, and complete instability. To help the reader and to show the flexibility and potentiality of the discrete approach to dynamics, many examples, numerical simulations, and figures have been included. The book is used as a reference material for courses at a doctoral or upper undergraduate level in mathematics and theoretical engineering.

This is the first book devoted to radiowave propagation over land and sea. Researchers and engineers involved in propagation studies and applications in communications, broadcasting, radar and remote sensing will find this volume invaluable.

Many of the most challenging problems in the applied sciences involve non-differentiable structures as well as partial differential operators, thus leading to non-smooth distributed parameter systems. This edited volume aims to establish a theoretical and numerical foundation and develop new algorithmic paradigms for the treatment of non-smooth phenomena and associated parameter influences. Other goals include the realization and further advancement of these concepts in the context of robust and hierarchical optimization, partial differential games, and nonlinear partial differential complementarity problems, as well as their validation in the context of complex applications. Areas for which applications are considered include optimal control of multiphase fluids and of superconductors, image processing, thermoforming, and the formation of rivers and networks. Chapters are written by leading researchers and present results obtained in the first funding phase of the DFG Special Priority Program on Nonsmooth and Complementarity Based Distributed Parameter Systems: Simulation and Hierarchical Optimization that ran from 2016 to 2019.

Wind energy systems are central contributors to renewable energy generation, and their technology is continuously improved and updated. Without losing sight of theory, Control of Large Wind Energy Systems demonstrates how to implement concrete control systems for modern wind turbines, explaining the reasons behind choices and decisions. This book provides an extended treatment of different control topics divided into three thematic parts including modelling, control and implementation. Solutions for real-life difficulties such as multi-parameter tuning of several controllers, curve fitting of nonlinear power curves, and filter design for concrete signals are also undertaken. Examples and a case study are included to illustrate the parametrization of models, the control systems design with problems and possible solutions. Advice for the selection of control laws, calculation of specific parameters, which are necessary for the control laws, as the sensitivity functions, is given, as well as an evaluation of control performance based on indices and load calculation. Control of Large Wind Energy Systems covers methodologies which are not usually found in literature on this topic, including fractional order PID and nonlinear PID for pitch control, peak shaving control and extremum seeking control for the generator control, yaw control and shutdown control. This makes it an ideal book for postgraduate students, researchers and industrial engineers in the field of wind turbine control. Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.

This book has a rather strange history. It began in spring 1989, thirteen years after our Systems Science Department at SUNY-Binghamton was established, when I was asked by a group of students in our doctoral program to have a meeting with them. The spokesman of the group, Cliff Joslyn, opened our meeting by stating its purpose. I can closely paraphrase what he said: "We called this meeting to discuss with you, as Chairman of the Department, a fundamental problem with our systems science curriculum. In general, we consider it a good curriculum: we learn a lot of concepts, principles, and methodological tools, mathematical, computational, heu ristic, which are fundamental to understanding and dealing with systems. And, yet, we learn virtually nothing about systems science itself. What is systems science? What are its historical roots? What are its aims? Where does it stand and where is it likely to go? These are pressing questions to us. After all, aren't we supposed to carry the systems science flag after we graduate from this program? We feel that a broad introductory course to systems science is urgently needed in the curriculum. Do you agree with this assessment?" The answer was obvious and, yet, not easy to give: "I agree, of course, but I do not see how the situation could be alleviated in the foreseeable future."

This book, dedicated to Professor Georgi M. Dimirovski on his anniversary, contains new research directions, challenges, and many relevant applications related to many aspects within the broadly perceived areas of systems and control, including signal analysis and intelligent systems. The project comprises two volumes with papers written by well known and very active researchers and practitioners. The first volume is focused on more foundational aspects related to general issues in systems science and mathematical systems, various problems in control and automation, and the use of computational and artificial intelligence in the context of systems modeling and control. The second volume is concerned with a presentation of relevant applications, notably in robotics, computer networks, telecommunication, fault detection/diagnosis, as well as in biology and medicine, and economic, financial, and social systems too.

Is knowledge an economic good? Which are the characteristics of the institutions regulating the production and diffusion of knowledge? Cumulation of knowledge is a key determinant of economic growth, but only recently knowledge has moved to the core of economic analysis. Recent literature also gives profound insights into events like scientific progress, artistic and craft development which have been rarely addressed as socio-economic institutions, being the domain of sociologists and historians rather than economists. This volume adopts a multidisciplinary approach to bring knowledge in the focus of attention, as a key economic issue.

This book explores a different pragmatic approach to algorithmic complexity rooted or motivated by the theoretical foundations of algorithmic probability and explores the relaxation of necessary and sufficient conditions in the pursuit of numerical applicability, with some of these approaches entailing greater risks than others in exchange for greater relevance and applicability. Some established and also novel techniques in the field of applications of algorithmic (Kolmogorov) complexity currently coexist for the first time, ranging from the dominant ones based upon popular statistical lossless compression algorithms (such as LZW) to newer approaches that advance, complement, and also pose their own limitations. Evidence suggesting that these different methods complement each other for different regimes is presented, and despite their many challenges, some of these methods are better grounded in or motivated by the principles of algorithmic information. The authors propose that the field can make greater contributions to science, causation, scientific discovery, networks, and cognition, to mention a few among many fields, instead of remaining either as a technical curiosity of mathematical interest only or as a statistical tool when collapsed into an application of popular lossless compression algorithms. This book goes, thus, beyond popular statistical lossless compression and introduces a different methodological approach to dealing with algorithmic complexity. For example, graph theory and network science are classic subjects in mathematics widely investigated in the twentieth century, transforming research in many fields of science from economy to medicine. However, it has become increasingly clear that the challenge of analyzing these networks cannot be addressed by tools relying solely on statistical methods. Therefore, model-driven approaches are needed. Recent advances in network science suggest that algorithmic information theory could play an increasingly important role in breaking those limits imposed by traditional statistical analysis (entropy or statistical compression) in modeling evolving complex networks or interacting networks. Further progress on this front calls for new techniques for an improved mechanistic understanding of complex systems, thereby calling out for increased interaction between systems science, network theory, and algorithmic information theory, to which this book contributes.

This volume presents an accessible overview of mathematical control theory and analysis of PDEs, providing young researchers a snapshot of these active and rapidly developing areas. The chapters are based on two mini-courses and additional talks given at the spring school "Trends in PDEs and Related Fields" held at the University of Sidi Bel Abbes, Algeria from 8-10 April 2019. In addition to providing an in-depth summary of these two areas, chapters also highlight breakthroughs on more specific topics such as: Sobolev spaces and elliptic boundary value problems Local energy solutions of the nonlinear wave equation Geometric control of eigenfunctions of Schroedinger operators Research in PDEs and Related Fields will be a valuable resource to graduate students and more junior members of the research community interested in control theory and analysis of PDEs.

Knowledge has in recent years become a key driver for growth of regions and nations. This volume empirically investigates the emergence of the knowledge economy in the late 20th century from a regional point of view. It first deals with the theoretical background for understanding the knowledge economy, with knowledge spillovers and development externalities. It then examines aspects of the relationship between knowledge inputs and innovative outputs in the information, computer and telecommunications sector (ICT) of the economy at the regional level. Case studies focusing on a wide variety of sectors, countries and regions finally illustrate important regional innovation issues.

How do we design a self-organizing system? Is it possible to validate and control non-deterministic dynamics? What is the right balance between the emergent patterns that bring robustness, adaptability and scalability, and the traditional need for verification and validation of the outcomes? The last several decades have seen much progress from original ideas of "emergent functionality" and "design for emergence", to sophisticated mathematical formalisms of "guided self-organization". And yet the main challenge remains, attracting the best scientific and engineering expertise to this elusive problem. This book presents state-of-the-practice of successfully engineered self-organizing systems, and examines ways to balance design and self-organization in the context of applications. As demonstrated in this second edition of Advances in Applied Self-Organizing Systems, finding this balance helps to deal with practical challenges as diverse as navigation of microscopic robots within blood vessels, self-monitoring aerospace vehicles, collective and modular robotics adapted for autonomous reconnaissance and surveillance, self-managing grids and multiprocessor scheduling, data visualization and self-modifying digital and analog circuitry, intrusion detection in computer networks, reconstruction of hydro-physical fields, traffic management, immunocomputing and nature-inspired computation. Many algorithms proposed and discussed in this volume are biologically inspired, and the reader will also gain an insight into cellular automata, genetic algorithms, artificial immune systems, snake-like locomotion, ant foraging, birds flocking, neuromorphic circuits, amongst others. Demonstrating the practical relevance and applicability of self-organization, Advances in Applied Self-Organizing Systems will be an invaluable tool for advanced students and researchers in a wide range of fields.

The basis for this book is a number of lectures given frequently by the author to third year students of the Department of Economics at Leningrad State University who specialize in economical cybernetics. The main purpose of this book is to provide the student with a relatively simple and easy-to-understand manual containing the basic mathematical machinery utilized in the theory of games. Practical examples (including those from the field of economics) serve mainly as an interpretation of the mathematical foundations of this theory rather than as indications of their actual or potential applicability. The present volume is significantly different from other books on the theory of games. The difference is both in the choice of mathematical problems as well as in the nature of the exposition. The realm of the problems is somewhat limited but the author has tried to achieve the greatest possible systematization in his exposition. Whenever possible the author has attempted to provide a game-theoretical argument with the necessary mathematical rigor and reasonable generality. Formal mathematical prerequisites for this book are quite modest. Only the elementary tools of linear algebra and mathematical analysis are used.

Nonlinear Stochastic Processes addresses the frequently-encountered problem of incomplete information. The causes of this problem considered here include: missing measurements; sensor delays and saturation; quantization effects; and signal sampling. Divided into three parts, the text begins with a focus on H filtering and control problems associated with general classes of nonlinear stochastic discrete-time systems. Filtering problems are considered in the second part, and in the third the theory and techniques previously developed are applied to the solution of issues arising in complex networks with the design of sampled-data-based controllers and filters. Among its highlights, the text provides: * a unified framework for filtering and control problems in complex communication networks with limited bandwidth; * new concepts such as random sensor and signal saturations for more realistic modeling; and * demonstration of the use of techniques such as the Hamilton-Jacobi-Isaacs, difference linear matrix, and parameter-dependent matrix inequalities and sums of squares to handle the computational challenges inherent in these systems. The collection of recent research results presented in Nonlinear Stochastic Processes will be of interest to academic researchers in control and signal processing. Graduate students working with communication networks with lossy information and control of stochastic systems will also benefit from reading the book.

This book uses a system-based approach to decipher and organize the concepts and conclusions relevant for creating and capturing value in business. It develops a scientific theory based on systems science and logical reasoning that is commonly employed in mathematics and natural science. The resulting new theory focuses on the organizational nature of the world and the organic and holistic feature of human organizations and their interactions. To this end, this book identifies a few axioms, instead of empirical discoveries, on which it reliably constructs the entire theory.

This book uses new ideas and language for understanding how self-organization and complexity trend toward increased efficiency. Different measures for efficiency from multiple disciplines are used to probe the ones that provide the most insight. One major goal is to seek a common framework to trace the increase of efficiency as a measure of the level of organization and evolutionary stage of a complex system. The chapters come from a satellite meeting hosted at the Conference on Complex Systems, in Cancun, 2017. The contributions will be peer-reviewed and contributors from outside the conference will be invited to submit chapters to ensure full coverage of the topics. This text will appeal to students and researchers working on complex systems and efficiency.

Written in the 1980s by one of the fathers of chaos theory, Otto E. Roessler, the manuscript presented in this volume eventually never got published. Almost 40 years later, it remains astonishingly at the forefront of knowledge about chaos theory and many of the examples discussed have never been published elsewhere. The manuscript has now been edited by Christophe Letellier - involved in chaos theory for almost three decades himself, as well as being active in the history of sciences - with a minimum of changes to the original text. Finally released for the benefit of specialists and non-specialists alike, this book is equally interesting from the historical and the scientific points of view: an unconventionally modern approach to chaos theory, it can be read as a classic introduction and short monograph as well as a collection of original insights into advanced topics from this field.

This book presents the dynamic modeling and attitude control of flexible spacecraft with time-varying parameters. The dynamic characteristics, vibration control methods and attitude stabilization methods for spacecraft are systematically studied in respects of the theoretical modeling, numerical simulation and the ground experiment. Three active control theories in complex mode space are presented for flexible space structures. Optimal slew strategies based on variable amplitudes input shaping methods and coupling control methods are proposed for stabilization of flexible spacecraft. The research provides an important way to solve the problem of high-precision attitude control of flexible spacecraft with time-varying parameters. This book is appropriate for the researchers who focus on the multi-body dynamics, attitude and vibration control of flexible spacecraft.

This book is devoted to the problem of sampled-data control of finite-dimensional linear continuous periodic (FDLCP) objects. It fills a deficit in coverage of this important subject. The methods presented here are based on the parametric transfer matrix, which has proven successful in the study of sampled-data systems with linear time-invariant objects. The book shows that this concept can be successfully transferred to sampled-data systems with FDLCP objects. It is set out in five parts: * * an introduction to the frequency approach for the mathematical description of FDLCP objects including the determination of their structure and their representation as a serial connection of periodic modulators and a linear time-invariant object; * construction of parametric transfer matrix for different types of open and closed sampled-data systems with FDLCP objects; * the solution of problems of causal modal control of FDLCP objects based on the mathematical apparatus of determinant polynomial equations; * consideration of the problem of constructing a quadratic quality functional for the H2-optimization problem of a single-loop synchronous sampled-data system with control delay; * description of the general H2-optimization procedure. Necessary mathematical reference material is included at relevant points in the book. Sampled-Data Control for Periodic Objects is of use to: scientists and engineers involved in research and design of systems of systems with FDLCP objects; graduate students wishing to broaden their scope of competence; their instructors; and mathematicians working in the field of control theory.

Cooperative Control Design: A Systematic, Passivity-Based Approach discusses multi-agent coordination problems, including formation control, attitude coordination, and synchronization. The goal of the book is to introduce passivity as a design tool for multi-agent systems, to provide exemplary work using this tool, and to illustrate its advantages in designing robust cooperative control algorithms. The discussion begins with an introduction to passivity and demonstrates how passivity can be used as a design tool for motion coordination. Followed by the case of adaptive redesigns for reference velocity recovery while describing a basic design, a modified design and the parameter convergence problem. Formation control is presented as it relates to relative distance control and relative position control. The coverage is concluded with a comprehensive discussion of agreement and the synchronization problem with an example using attitude coordination.