Discrete Networked Dynamic Systems: Analysis and Performance provides a high-level treatment of a general class of linear discrete-time dynamic systems interconnected over an information network, exchanging relative state measurements or output measurements. It presents a systematic analysis of the material and provides an account to the math development in a unified way. The topics in this book are structured along four dimensions: Agent, Environment, Interaction, and Organization, while keeping global (system-centered) and local (agent-centered) viewpoints. The focus is on the wide-sense consensus problem in discrete networked dynamic systems. The authors rely heavily on algebraic graph theory and topology to derive their results. It is known that graphs play an important role in the analysis of interactions between multiagent/distributed systems. Graph-theoretic analysis provides insight into how topological interactions play a role in achieving coordination among agents. Numerous types of graphs exist in the literature, depending on the edge set of G. A simple graph has no self-loop or edges. Complete graphs are simple graphs with an edge connecting any pair of vertices. The vertex set in a bipartite graph can be partitioned into disjoint non-empty vertex sets, whereby there is an edge connecting every vertex in one set to every vertex in the other set. Random graphs have fixed vertex sets, but the edge set exhibits stochastic behavior modeled by probability functions. Much of the studies in coordination control are based on deterministic/fixed graphs, switching graphs, and random graphs.

In the era of cyber-physical systems, the area of control of complex systems has grown to be one of the hardest in terms of algorithmic design techniques and analytical tools. The 23 chapters, written by international specialists in the field, cover a variety of interests within the broader field of learning, adaptation, optimization and networked control. The editors have grouped these into the following 5 sections: "Introduction and Background on Control Theory", "Adaptive Control and Neuroscience", "Adaptive Learning Algorithms", "Cyber-Physical Systems and Cooperative Control", "Applications". The diversity of the research presented gives the reader a unique opportunity to explore a comprehensive overview of a field of great interest to control and system theorists. This book is intended for researchers and control engineers in machine learning, adaptive control, optimization and automatic control systems, including Electrical Engineers, Computer Science Engineers, Mechanical Engineers, Aerospace/Automotive Engineers, and Industrial Engineers. It could be used as a text or reference for advanced courses in complex control systems. * Collection of chapters from several well-known professors and researchers that will showcase their recent work * Presents different state-of-the-art control approaches and theory for complex systems * Gives algorithms that take into consideration the presence of modelling uncertainties, the unavailability of the model, the possibility of cooperative/non-cooperative goals and malicious attacks compromising the security of networked teams * Real system examples and figures throughout, make ideas concrete

Industry 4.0 and the subsequent automation and digitalization of processes, including the tighter integration of machine-machine and human-machine intercommunication and collaboration, is adding additional complexity to future systems design and the capability to simulate, optimize, and adapt. Current solutions lack the ability to capture knowledge, techniques, and methods to create a sustainable and intelligent nerve system for enterprise systems. With the ability to innovate new designs and solutions, as well as automate processes and decision-making capabilities with heterogenous and holistic views of current and future challenges, there can be an increase in productivity and efficiency through sustainable automation. Therefore, better understandings of the underpinning knowledge and expertise of sustainable automation that can create a sustainable cycle that drives optimal automation and innovation in the field is needed Driving Innovation and Productivity Through Sustainable Automation enhances the understanding and the knowledge for the new ecosystems emerging in the Fourth Industrial Revolution. The chapters provide the knowledge and understanding of current challenges and new capabilities and solutions having been researched, developed, and applied within the industry to drive sustainable automation for innovation and productivity. This book is ideally intended for managers, executives, IT specialists, practitioners, stakeholders, researchers, academicians, and students who are interested in the current research on sustainable automation.

The current literature on dynamic systems is quite comprehensive, and system theory's mathematical jargon can remain quite complicated. Thus, there is a need for a compendium of accessible research that involves the broad range of fields that dynamic systems can cover, including engineering, life sciences, and the environment, and which can connect researchers in these fields. The Handbook of Research on Modeling, Analysis, and Control of Complex Systems is a comprehensive reference book that describes the recent developments in a wide range of areas including the modeling, analysis, and control of dynamic systems, as well as explores related applications. The book acts as a forum for researchers seeking to understand the latest theory findings and software problem experiments. Covering topics that include chaotic maps, predictive modeling, random bit generation, and software bug prediction, this book is ideal for professionals, academicians, researchers, and students in the fields of electrical engineering, computer science, control engineering, robotics, power systems, and biomedical engineering.

This book covers the most important issues from classical and robust control, deterministic and stochastic control, system identification, and adaptive and iterative control strategies. It covers most of the known control system methodologies using a new base, the Youla parameterization (YP). This concept is introduced and extended for TDOF control loops. The Keviczky-Banyasz parameterization (KP) method developed for closed loop systems is also presented. The book is valuable for those who want to see through the jungle of available methods by using a unified approach, and for those who want to prepare computer code with a given algorithm.

A comprehensive exploration of the control schemes of human-robot interactions In Human-Robot Interaction Control Using Reinforcement Learning, an expert team of authors delivers a concise overview of human-robot interaction control schemes and insightful presentations of novel, model-free and reinforcement learning controllers. The book begins with a brief introduction to state-of-the-art human-robot interaction control and reinforcement learning before moving on to describe the typical environment model. The authors also describe some of the most famous identification techniques for parameter estimation. Human-Robot Interaction Control Using Reinforcement Learning offers rigorous mathematical treatments and demonstrations that facilitate the understanding of control schemes and algorithms. It also describes stability and convergence analysis of human-robot interaction control and reinforcement learning based control. The authors also discuss advanced and cutting-edge topics, like inverse and velocity kinematics solutions, H2 neural control, and likely upcoming developments in the field of robotics. Readers will also enjoy: A thorough introduction to model-based human-robot interaction control Comprehensive explorations of model-free human-robot interaction control and human-in-the-loop control using Euler angles Practical discussions of reinforcement learning for robot position and force control, as well as continuous time reinforcement learning for robot force control In-depth examinations of robot control in worst-case uncertainty using reinforcement learning and the control of redundant robots using multi-agent reinforcement learning Perfect for senior undergraduate and graduate students, academic researchers, and industrial practitioners studying and working in the fields of robotics, learning control systems, neural networks, and computational intelligence, Human-Robot Interaction Control Using Reinforcement Learning is also an indispensable resource for students and professionals studying reinforcement learning.

Handbook of Robotic and Image-Guided Surgery provides state-of-the-art systems and methods for robotic and computer-assisted surgeries. In this masterpiece, contributions of 169 researchers from 19 countries have been gathered to provide 38 chapters. This handbook is 744 pages, includes 659 figures and 61 videos. It also provides basic medical knowledge for engineers and basic engineering principles for surgeons. A key strength of this text is the fusion of engineering, radiology, and surgical principles into one book.

This book is designed primarily as a laboratory operations manual for fundamental mechatronics and robotics experiential and project-based learning. It is also ordered in that starting with the Tricycle Robot, students build up their knowledge and experience of programming to be able to tackle the Rickshaw Robot and finally the most complex robot, i.e., the Hexapod Robot. The book is aimed at university and college students; however, with robotics curricula extending down into lower grades this book can also be very useful for teachers at any school level. Furthermore, the book provides useful ideas for driverless vehicles and robots, as well as for educators who are developing practical project-based teaching and learning modules. Readers of the book can easily modify the coding, computing language, and hardware to suit personal preferences.

The monograph provides an overview of the recent developments in modern control systems including new theoretical finding and successful examples of practical implementation of the control theory in different areas of industrial and special applications. Recent Developments in Automatic Control Systems consists of extended versions of the selected papers presented at XXVI International Conference on Automatic Control "Automation 2020" (October 13-15, 2020, Kyiv, Ukraine) which is the main Ukrainian Control Conference organized by Ukrainian Association on Automatic Control (National member organization of IFAC) and National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute". This is a third monograph in the River Publishers series in Automation, Control and Robotics, which is publishing based on the selected papers of the Ukrainian Control Conferences "Automation", in particular, first monograph "Control Systems: Theory and Applications (2018) was published based on the "Automation - 2017" and second monograph "Advanced Control Systems: Theory and Applications" - based on the "Automation - 2018". The monograph is divided into three main parts: (a) Advances in Theoretical Research of Control Systems; (b) Advances in Control Systems Application; (c) Recent Developments in Collaborative Automation. The chapters have been structured to provide an easy-to-follow introduction to the topics that are addressed, including the most relevant references, so that anyone interested in this field can get started in the area. This book may be useful for researchers and students who are interesting in recent developments of the modern control systems, robust adaptive systems, optimal control, fuzzy control, motion control, identification, modelling, differential games, evolutionary optimization, reliability control, security control, intelligent robotics and cyber-physical systems.

"Introduction to Mobile Robot Control" provides a complete and concise study of modeling, control, and navigation methods for wheeled non-holonomic and omnidirectional mobile robots and manipulators. The book begins with a study of mobile robot drives and corresponding kinematic and dynamic models, and discusses the sensors used in mobile robotics. It then examines a variety of model-based, model-free, and vision-based controllers with unified proof of their stabilization and tracking performance, also addressingthe problems of path, motion, and task planning, along with localization and mapping topics. The book provides a host of experimental results, a conceptual overview of systemic and software mobile robot control architectures, and a tour of the use of wheeled mobile robots and manipulators in industry and society.

"Introduction to Mobile Robot Control" is an essential reference, and is also a textbook suitable as a supplement for many university robotics courses. It is accessible to all and can be used as a reference for professionals and researchers in the mobile robotics field.
Clearly and authoritatively presents mobile robot conceptsRichly illustrated throughout with figures and examplesKey concepts demonstrated with a host of experimental and simulation examplesNo prior knowledge of the subject is required; each chapter commences with an introduction and background"

Fractional Order Systems: Optimization, Control, Circuit Realizations and Applications consists of 21 contributed chapters by subject experts. Chapters offer practical solutions and novel methods for recent research problems in the multidisciplinary applications of fractional order systems, such as FPGA, circuits, memristors, control algorithms, photovoltaic systems, robot manipulators, oscillators, etc. This book is ideal for researchers working in the modeling and applications of both continuous-time and discrete-time dynamics and chaotic systems. Researchers from academia and industry who are working in research areas such as control engineering, electrical engineering, mechanical engineering, computer science, and information technology will find the book most informative.

While human capabilities can withstand broad levels of strain, they cannot hope to compete with the advanced abilities of automated technologies. Developing advanced robotic systems will provide a better, faster means to produce goods and deliver a level of seamless communication and synchronization that exceeds human skill. Advanced Robotics and Intelligent Automation in Manufacturing is a pivotal reference source that provides vital research on the application of advanced manufacturing technologies in regards to production speed, quality, and innovation. While highlighting topics such as human-machine interaction, quality management, and sensor integration, this publication explores state-of-the-art technologies in the field of robotics engineering as well as human-robot interaction. This book is ideally designed for researchers, students, engineers, manufacturers, managers, industry professionals, and academicians seeking to enhance their innovative design capabilities.

This book focuses on transmission systems for pure electric and hybrid vehicles. It first discusses system development and optimization technologies, comprehensively and systematically describing the development trends, structures and technical characteristics, as well as the related technologies and methods. It highlights the principles, implementation process and energy management of the power transmission system based on the pure electric and hybrid mode management method, and examines the reliability and NVH characteristic tests and optimization technologies. Combining research theory and engineering practice, the book is a valuable reference resource for engineering and technical professionals in the field of automobile and related power transmission machinery as well as undergraduate and graduate students.

Robots have come a long way thanks to advances in sensing and computer vision technologies and can be found today in healthcare, medicine and industry. Researchers have been looking at providing them with senses such as the ability to see, smell, hear and perceive touch in order to mimic and interact with humans and their surrounding environments. Topics covered in this edited book include various types of sensors used in robotics, sensing schemes (e-skin, tactile skin, e-nose, neuromorphic vision and touch), sensing technologies and their applications including healthcare, prosthetics, robotics and wearables. This book will appeal to researchers, scientists, engineers, and graduate and advanced students working in robotics, sensor technologies and electronics, and their applications in robotics, haptics, prosthetics, wearable and interactive systems, cognitive engineering, neuro-engineering, computational neuroscience, medicine and healthcare technologies.