This book presents the state of the art in distributed autonomous systems composed of multiple robots, robotic modules, or robotic agents. Swarms in nature can not only adapt to their environments, but can also construct suitable habitats to their own advantage. Distributed autonomous robotic systems can do many things that its individuals cannot do alone. As the global pandemic was still ongoing, the 15th International Symposium on Distributed Autonomous Robotic Systems (DARS2021) was held on June 1-4, 2021, as an online meeting. The scope of DARS201 was to create a bridge between biologists and engineers interested in the distributed intelligence of living things and to establish a new academic field by integrating knowledge from both disciplines. Topics of DARS2021 were swarm intelligence, swarm robotics, multi-agent system, modular robotics, decentralized control, distributed system, etc. The papers in this book provide a very good overview of the state of the art in distributed autonomous robotic systems (DARS). They reflect current research themes in DARS with important contributions. We hope that this book helps to sustain the interest in DARS and triggers new research.

This open access book presents research and evaluation results of the Austrian flagship project "Connecting Austria," illustrating the wide range of research needs and questions that arise when semi-automated truck platooning is deployed in Austria. The work presented is introduced in the context of work in similar research areas around the world. This interdisciplinary research effort considers aspects of engineering, road-vehicle and infrastructure technologies, traffic management and optimization, traffic safety, and psychology, as well as potential economic effects. The book's broad perspective means that readers interested in current and state-of-the-art methods and techniques for the realization of semi-automated driving and with either an engineering background or with a less technical background gain a comprehensive picture of this important subject. The contributors address many questions such as: Which maneuvers does a platoon typically have to carry out, and how? How can platoons be integrated seamlessly in the traffic flow without becoming an obstacle to individual road users? What trade-offs between system information (sensors, communication effort, etc.) and efficiency are realistic? How can intersections be passed by a platoon in an intelligent fashion? Consideration of diverse disciplines and highlighting their meaning for semi-automated truck platooning, together with the highlighting of necessary research and evaluation patterns to address such a broad task scientifically, makes Energy-Efficient and Semi-automated Truck Platooning a unique contribution with methods that can be extended and adapted beyond the geographical area of the research reported.

This book is inspired by the development of distributed model predictive control of networked systems to save computation and communication sources. The significant new contribution is to show how to design efficient DMPCs that can be coordinated asynchronously with the increasing effectiveness of the event-triggering mechanism and how to improve the event-triggered DMPC for different requirements improvement of control performance, extension to interconnected networked systems, etc. The book is likely to be of interest to the persons who are engaged in researching control theory in academic institutes, the persons who go in for developing control systems in R&D institutes or companies, the control engineers who are engaged in the implementation of control algorithms, and people who are interested in the distributed MPC.

Artificial intelligence and related technologies are changing both the law and the legal profession. In particular, technological advances in fields ranging from machine learning to more advanced robots, including sensors, virtual realities, algorithms, bots, drones, self-driving cars, and more sophisticated "human-like" robots are creating new and previously unimagined challenges for regulators. These advances also give rise to new opportunities for legal professionals to make efficiency gains in the delivery of legal services. With the exponential growth of such technologies, radical disruption seems likely to accelerate in the near future. This collection brings together a series of contributions by leading scholars in the newly emerging field of artificial intelligence, robotics, and the law. The aim of the book is to enrich legal debates on the social meaning and impact of this type of technology. The distinctive feature of the contributions presented in this edition is that they address the impact of these technological developments in a number of different fields of law and from the perspective of diverse jurisdictions. Moreover, the authors utilize insights from multiple related disciplines, in particular social theory and philosophy, in order to better understand and address the legal challenges created by AI. Therefore, the book will contribute to interdisciplinary debates on disruptive new AI technologies and the law.

China Satellite Navigation Conference (CSNC 2022) Proceedings presents selected research papers from CSNC 2022 held during 22nd-25th May, 2022 in Beijing, China. These papers discuss the technologies and applications of the Global Navigation Satellite System (GNSS), and the latest progress made in the China BeiDou System (BDS) especially. They are divided into 10 topics to match the corresponding sessions in CSNC2022 which broadly covered key topics in GNSS. Readers can learn about the BDS and keep abreast of the latest advances in GNSS techniques and applications.

This book addresses problems in the modeling, detection, and control of emergent behaviors and task coordination in multiagent systems. It presents a unified solution to such problems in terms of distributed estimation, distributed control, and optimization of interaction topologies and dynamics. Four aspects of the technical solutions in the book are presented: First, the impact of interaction dynamics on the convergence conditions related to interaction topologies is discussed, utilizing a discontinuous cooperative control algorithm of updated design. Second, distributed least-squares and Kalman filtering algorithms for agents with limited interactions are elaborated upon. Third, a general framework of distributed nonlinear control is established, and distributed adaptive control for nonlinear systems with more general uncertainties is presented. Based on the proposed framework, a distributed nonlinear controller is designed to deal with task coordination of robotic systems with nonholonomic constraints. Finally, the problem of optimal multiagent task coordination is addressed and solutions based on approximate dynamic programming and approximate distributed gradient estimation are presented. Emergent Behavior Detection and Task Coordination for Multiagent Systems is of interest to practicing engineers in areas such as robotics and cyber-physical systems, researchers in the field of systems, controls, and robotics, and senior undergraduate and graduate students.

Previous research on fixed/finite-time sliding-mode control focuses on forcing a system state (vector) to converge within a certain time moment, regardless of how each state element converges. This book introduces a control problem with unique finite/fixed-time stability considerations, namely time-synchronized stability, where at the same time, all the system state elements converge to the origin, and fixed-time-synchronized stability, where the upper bound of the synchronized settling time is invariant with any initial state. Accordingly, sufficient conditions for (fixed-) time-synchronized stability are presented. These stability formulations grant essentially advantageous performance when a control system (with diversified subsystems) is expected to accomplish multiple actions synchronously, e.g., grasping with a robotic hand, multi-agent simultaneous cooperation, etc. Further, the analytical solution of a (fixed) time-synchronized stable system is obtained and discussed. Applications to linear systems, disturbed nonlinear systems, and network systems are provided. In addition, comparisons with traditional fixed/finite-time sliding mode control are suitably detailed to showcase the full power of (fixed-) time-synchronized control.

This book illustrates the main characteristics, challenges and optimisation requirements of robotic disassembly. It provides a comprehensive insight on two crucial optimisation problems in the areas of robotic disassembly through a group of unified mathematical models. The online and offline optimisation of the operational sequence to dismantle a product, for example, is represented with a list of conflicting objectives and constraints. It allows the decision maker and the robots to match the situation automatically and efficiently. To identify a generic solution under different circumstances, classical metaheuristics that can be used for the optimisation of robotic disassembly are introduced in detail. A flexible framework is then presented to implement existing metaheuristics for sequence planning and line balancing in the circumstance of robotic disassembly. Optimisation of Robotic Disassembly for Remanufacturing provides practical case studies on typical product instances to help practitioners design efficient robotic disassembly with minimal manual operation, and offers comparisons of the state-of-the-art metaheuristics on solving the key optimisation problems. Therefore, it will be of interest to engineers, researchers, and postgraduate students in the area of remanufacturing.

This book highlights various evolutionary algorithm techniques for various medical conditions and introduces medical applications of evolutionary computation for real-time diagnosis. Evolutionary Intelligence for Healthcare Applications presents how evolutionary intelligence can be used in smart healthcare systems involving big data analytics, mobile health, personalized medicine, and clinical trial data management. It focuses on emerging concepts and approaches and highlights various evolutionary algorithm techniques used for early disease diagnosis, prediction, and prognosis for medical conditions. The book also presents ethical issues and challenges that can occur within the healthcare system. Researchers, healthcare professionals, data scientists, systems engineers, students, programmers, clinicians, and policymakers will find this book of interest.

Graph Theory and Its Applications, Third Edition is the latest edition of the international, bestselling textbook for undergraduate courses in graph theory, yet it is expansive enough to be used for graduate courses as well. The textbook takes a comprehensive, accessible approach to graph theory, integrating careful exposition of classical developments with emerging methods, models, and practical needs. The authors' unparalleled treatment is an ideal text for a two-semester course and a variety of one-semester classes, from an introductory one-semester course to courses slanted toward classical graph theory, operations research, data structures and algorithms, or algebra and topology. Features of the Third Edition Expanded coverage on several topics (e.g., applications of graph coloring and tree-decompositions) Provides better coverage of algorithms and algebraic and topological graph theory than any other text Incorporates several levels of carefully designed exercises that promote student retention and develop and sharpen problem-solving skills Includes supplementary exercises to develop problem-solving skills, solutions and hints, and a detailed appendix, which reviews the textbook's topics About the Authors Jonathan L. Gross is a professor of computer science at Columbia University. His research interests include topology and graph theory. Jay Yellen is a professor of mathematics at Rollins College. His current areas of research include graph theory, combinatorics, and algorithms. Mark Anderson is also a mathematics professor at Rollins College. His research interest in graph theory centers on the topological or algebraic side.

"Compensating for Quasi-periodic Motion in Robotic Radiosurgery" outlines the techniques needed to accurately track and compensate for respiratory and pulsatory motion during robotic radiosurgery. The algorithms presented within the book aid in the treatment of tumors that move during respiration.
In Chapters 1 and 2, the book introduces the concept of stereotactic body radiation therapy, motion compensation strategies and the clinical state-of-the-art. In Chapters 3 through 5, the author describes and evaluates new methods for motion prediction, for correlating external motion to internal organ motion, and for the evaluation of these algorithms' output based on an unprecedented amount of real clinical data. Finally, Chapter 6 provides a brief introduction into currently investigated, open questions and further fields of research.
"Compensating for Quasi-periodic Motion in Robotic Radiosurgery" targets researchers working in the related fields of surgical oncology, artificial intelligence, robotics and more. Advanced-level students will also find this book valuable."

Autonomous underwater vehicles (AUVs) are emerging as a promising solution to help us explore and understand the ocean. The global market for AUVs is predicted to grow from 638 million dollars in 2020 to 1,638 million dollars by 2025 - a compound annual growth rate of 20.8 percent. To make AUVs suitable for a wider range of application-specific missions, it is necessary to deploy multiple AUVs to cooperatively perform the localization, tracking and formation tasks. However, weak underwater acoustic communication and the model uncertainty of AUVs make achieving this challenging. This book presents cutting-edge results regarding localization, tracking and formation for AUVs, highlighting the latest research on commonly encountered AUV systems. It also showcases several joint localization and tracking solutions for AUVs. Lastly, it discusses future research directions and provides guidance on the design of future localization, tracking and formation schemes for AUVs. Representing a substantial contribution to nonlinear system theory, robotic control theory, and underwater acoustic communication system, this book will appeal to university researchers, scientists, engineers, and graduate students in control theory and control engineering who wish to learn about the core principles, methods, algorithms, and applications of AUVs. Moreover, the practical localization, tracking and formation schemes presented provide guidance on exploring the ocean. The book is intended for those with an understanding of nonlinear system theory, robotic control theory, and underwater acoustic communication systems.

The main focus of this book is a pair of cooperative control problems: consensus and cooperative output regulation. Its emphasis is on complex multi-agent systems characterized by strong nonlinearity, large uncertainty, heterogeneity, external disturbances and jointly connected switching communication topologies. The cooperative output regulation problem is a generalization of the classical output regulation problem to multi-agent systems and it offers a general framework for handling a variety of cooperative control problems such as consensus, formation, tracking and disturbance rejection. The book strikes a balance between rigorous mathematical proof and engineering practicality. Every design method is systematically presented together with illustrative examples and all the designs are validated by computer simulation. The methods presented are applied to several practical problems, among them the leader-following consensus problem of multiple Euler-Lagrange systems, attitude synchronization of multiple rigid-body systems, and power regulation of microgrids. The book gives a detailed exposition of two approaches to the design of distributed control laws for complex multi-agent systems-the distributed-observer and distributed-internal-model approaches. Mastering both will enhance a reader's ability to deal with a variety of complex real-world problems. Cooperative Control of Multi-agent Systems can be used as a textbook for graduate students in engineering, sciences, and mathematics, and can also serve as a reference book for practitioners and theorists in both industry and academia. Some knowledge of the fundamentals of linear algebra, calculus, and linear systems are needed to gain maximum benefit from this book. 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.

Focused on the mathematical foundations of social media analysis, Graph-Based Social Media Analysis provides a comprehensive introduction to the use of graph analysis in the study of social and digital media. It addresses an important scientific and technological challenge, namely the confluence of graph analysis and network theory with linear algebra, digital media, machine learning, big data analysis, and signal processing. Supplying an overview of graph-based social media analysis, the book provides readers with a clear understanding of social media structure. It uses graph theory, particularly the algebraic description and analysis of graphs, in social media studies. The book emphasizes the big data aspects of social and digital media. It presents various approaches to storing vast amounts of data online and retrieving that data in real-time. It demystifies complex social media phenomena, such as information diffusion, marketing and recommendation systems in social media, and evolving systems. It also covers emerging trends, such as big data analysis and social media evolution. Describing how to conduct proper analysis of the social and digital media markets, the book provides insights into processing, storing, and visualizing big social media data and social graphs. It includes coverage of graphs in social and digital media, graph and hyper-graph fundamentals, mathematical foundations coming from linear algebra, algebraic graph analysis, graph clustering, community detection, graph matching, web search based on ranking, label propagation and diffusion in social media, graph-based pattern recognition and machine learning, graph-based pattern classification and dimensionality reduction, and much more. This book is an ideal reference for scientists and engineers working in social media and digital media production and distribution. It is also suitable for use as a textbook in undergraduate or graduate courses on digital media, social media, or social networks.

Fully Tuned Radial Basis Function Neural Networks for Flight Control presents the use of the Radial Basis Function (RBF) neural networks for adaptive control of nonlinear systems with emphasis on flight control applications. A Lyapunov synthesis approach is used to derive the tuning rules for the RBF controller parameters in order to guarantee the stability of the closed loop system. Unlike previous methods that tune only the weights of the RBF network, this book presents the derivation of the tuning law for tuning the centers, widths, and weights of the RBF network, and compares the results with existing algorithms. It also includes a detailed review of system identification, including indirect and direct adaptive control of nonlinear systems using neural networks. Fully Tuned Radial Basis Function Neural Networks for Flight Control is an excellent resource for professionals using neural adaptive controllers for flight control applications.

This book is concerned with the development of the understanding of the relational structures of information, knowledge, decision-choice processes of problems and solutions in the theory and practice regarding diversity and unity principles of knowing, science, non-science, and information-knowledge systems through dualistic-polar conditions of variety existence and nonexistence. It is a continuation of the sequence of my epistemic works on the theories on fuzzy rationality, info-statics, info-dynamics, entropy, and their relational connectivity to information, language, knowing, knowledge, cognitive practices relative to variety identification-problem-solution dualities, variety transformation-problem-solution dualities, and variety certainty-uncertainty principle in all areas of knowing and human actions regarding general social transformations. It is also an economic-theoretic approach in understanding the diversity and unity of knowing and science through neuro-decision-choice actions over the space of problem-solution dualities and polarities. The problem-solution dualities are argued to connect all areas of knowing including science and non-science, social science, and non-social-science into unity with diversities under neuro-decision-choice actions to support human existence and nonexistence over the space of static-dynamic dualities. The concepts of diversity and unity are defined and explicated to connect to the tactics and strategies of decision-choice actions over the space of problem-solution dualities. The concepts of problem and solution are defined and explicated not in the space of absoluteness but rather in the space of relativity based on real cost-benefit conditions which are shown to be connected to the general parent-offspring infinite process, where every solution generates new problem(s) which then generates a search for new solutions within the space of minimum-maximum dualities in the decision-choice space under the principle of non-satiation over the space of preference-non-preference dualities with analytical tools drawn from the fuzzy paradigm of thought which connects the conditions of the principle of opposites to the conditions of neuro-decision-choice actions in the zone of variety identifications and transformations. The Monograph would be useful to all areas of Research, Learning and Teaching at Advanced Stages of Knowing and Knowledge Production.

Explores the history of telepresence from the 1948 developments of master-slave manipulation, through to current telepresence technology used in space, undersea, surgery and telemedicine, operations in nuclear and other hazardous environments, policing and surveillance, agriculture, construction, mining, warehousing, education, amusement, social media and other contexts Reviews the differing technologies for visual, haptic, tactile remote sensing at the remote site, and the corresponding means of the display to the human operator Reviews the sensing and control technology, its history, and likely future, and discusses the many research and policy issues Reviews psychological experiments in telepresence with relation to virtual and augmented reality Examines social and ethical concerns: ease of spying, mischief, and crime via remote control of an avatar

This book presents the fundamentals of arc phenomena, various arc welding power sources, their control strategies, welding data acquisition, and welding optimization. In addition, it discusses a broad range of electrical concepts in welding, including power source characteristics, associated parameters, arc welding power source classification, control strategies, data acquisitions techniques, as well as optimization methods. It also offers advice on how to minimize the flaws and improve the efficacy and performance of welds, as well as insights into the mechanical behavior expressed in terms of electromagnetic phenomena, which is rarely addressed. The book provides a comprehensive review of interdisciplinary concepts, offering researchers a wide selection of strategies, parameters, and sequences of operations to choose from.

The efforts in nonlinear control over the last few years have led to the level of generality in which conceptual solutions exist for all systems affine in control and the disturbance, and constructive designs exist for a specific class of nonlinear systems - although broad in terms of physical relevance. This monograph presents the fundamentals of global stabilization and optimal control of nonlinear systems with uncertain models. It offers a unified view of deterministic disturbance attenuation, stochastic control, and adaptive control for nonlinear systems. The book addresses a large audience of researchers, students, engineers and mathematicians in the areas of robust and adaptive nonlinear control, nonlinear H... stochastic nonlinear control (including risk-sensitive), and other related areas of control an d dynamical systems theory.

This book presents research related to smart devices and Internet of Things (IoT) that are intended to advance environmental sustainability. With sustainability as the focus, the topics covered include designing and controlling of smart systems, networking and machine learning, monitoring and controlling the environment, smart metering, authentication and authorization, and software and systems solution. The authors discuss how IoT can aid in sustainability through its implementation of systems interconnecting several objects, whether in the physical or in the virtual worlds. The chapters also present several applications including in smart homes, transportation, and healthcare. The book pertains to researchers, academics, and professionals.

"A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations of Bayesian analysis in the simplest of settings, and goes all the way to the frontiers of the subject such as infinite mixture models, GPs, and MCMC." -Devdatt Dubhashi, Professor, Department of Computer Science and Engineering, Chalmers University, Sweden "This textbook manages to be easier to read than other comparable books in the subject while retaining all the rigorous treatment needed. The new chapters put it at the forefront of the field by covering topics that have become mainstream in machine learning over the last decade." -Daniel Barbara, George Mason University, Fairfax, Virginia, USA "The new edition of A First Course in Machine Learning by Rogers and Girolami is an excellent introduction to the use of statistical methods in machine learning. The book introduces concepts such as mathematical modeling, inference, and prediction, providing 'just in time' the essential background on linear algebra, calculus, and probability theory that the reader needs to understand these concepts." -Daniel Ortiz-Arroyo, Associate Professor, Aalborg University Esbjerg, Denmark "I was impressed by how closely the material aligns with the needs of an introductory course on machine learning, which is its greatest strength...Overall, this is a pragmatic and helpful book, which is well-aligned to the needs of an introductory course and one that I will be looking at for my own students in coming months." -David Clifton, University of Oxford, UK "The first edition of this book was already an excellent introductory text on machine learning for an advanced undergraduate or taught masters level course, or indeed for anybody who wants to learn about an interesting and important field of computer science. The additional chapters of advanced material on Gaussian process, MCMC and mixture modeling provide an ideal basis for practical projects, without disturbing the very clear and readable exposition of the basics contained in the first part of the book." -Gavin Cawley, Senior Lecturer, School of Computing Sciences, University of East Anglia, UK "This book could be used for junior/senior undergraduate students or first-year graduate students, as well as individuals who want to explore the field of machine learning...The book introduces not only the concepts but the underlying ideas on algorithm implementation from a critical thinking perspective." -Guangzhi Qu, Oakland University, Rochester, Michigan, USA

This book focuses on vibration suppression of flexible three-dimensional Euler-Bernoulli beams modeled by PDEs. Boundary control strategy and several control methods are proposed to stabilize the closed-loop system. Besides, some common engineering problems such as input constraint and output constraint are also considered in the control scheme design. This book offers a comprehensive introduction of the modeling process, controller design, stability analysis and numerical simulation. The detailed MATLAB codes in each chapter are also provided, which can make readers better understand the control flow of the system. This book is mainly targeted for researchers, senior undergraduate students and postgraduate students in the field of control theory and control engineering.

This book presents the proceedings of the 4th International Conference of IFToMM ITALY (IFIT), held in Naples, Italy on September 7-9, 2022. It includes peer-reviewed papers on the latest advances in mechanism and machine science, discussing topics such as biomechanical engineering, computational kinematics, the history of mechanism and machine science, gearing and transmissions, multi-body dynamics, robotics and mechatronics, the dynamics of machinery, tribology, vibrations, rotor dynamics and vehicle dynamics. A valuable, up-to-date resource, it offers an essential overview of the subject for scientists and practitioners alike, and will inspire further investigations and research.

"Symmetries and Semi-invariants in the Analysis of Nonlinear Systems" details the analysis of continuous- and discrete-time dynamical systems described by differential and difference equations respectively. Differential geometry provides the essential tools for the analysis, tools such as first-integrals or orbital symmetries, together with normal forms of vector fields and of maps. The use of such tools allows the solution of some important problems, studied in detail in the text, which includelinearization by state immersionand the computation of nonlinear superposition formulae for nonlinear systems described by solvable Lie algebras.

The theory is developed for general nonlinear systems and, in view of their importance for modeling physical systems, specialized for the class of Hamiltonian systems. By using the strong geometric structure of Hamiltonian systems, the results proposed are stated in a quite different, less complex and more easily comprehensible manner. Throughout the text the results are illustrated by many examples, some of them being physically motivated systems, so that the reader can appreciate how much insight is gained by means of these techniques. Various control systems applications of the techniques are characterized including:

. computation of the flow of nonlinear systems;

. computation of semi-invariants;

. computation of Lyapunov functions for stability analysis.

"Symmetries and Semi-invariants in the Analysis of Nonlinear Systems" will be of interest to researchers and graduate students studying control theory, particularly with respect to nonlinear systems. All the necessary background and mathematical derivations are related in detail but in a simple writing style that makes the book accessible in depth to readers having a standard knowledge of real analysis, linear algebra and systems theory. "

Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems presents basic statistical process monitoring, fault diagnosis, and control methods, and introduces advanced data-driven schemes for the design of fault diagnosis and fault-tolerant control systems catering to the needs of dynamic industrial processes. With ever increasing demands for reliability, availability and safety in technical processes and assets, process monitoring and fault-tolerance have become important issues surrounding the design of automatic control systems. This text shows the reader how, thanks to the rapid development of information technology, key techniques of data-driven and statistical process monitoring and control can now become widely used in industrial practice to address these issues. To allow for self-contained study and facilitate implementation in real applications, important mathematical and control theoretical knowledge and tools are included in this book. Major schemes are presented in algorithm form and demonstrated on industrial case systems.Data-driven Design of Fault Diagnosis and Fault-tolerant Control Systems will be of interest to process and control engineers, engineering students and researchers with a control engineering background.