Swarm system, also known as multi-agent system, refers to a system composed of multiple subsystems (agents) with certain communication, calculation, decision-making, and action capabilities through local information interaction, such as a group of unmanned aerial vehicles (UAVs), unmanned ground vehicles (UGVs), satellites, etc. Formation tracking control of swarm systems is an important technical support and approach for the emergence of swarm intelligence at motion control level. By applying formation tracking control, swarm system agents can adjust their relations in the state or output space through neighboring information interaction, and then the swarm system can achieve favorable space-time conditions for many cooperative tasks such as source seeking, target enclosing, and surveillance. Thus, complex missions can be performed efficiently or cost-effectively. In cross-domain collaborative applications, including air-ground coordination and air-sea coordination, swarm systems are usually composed of several heterogeneous agents, and swarm intelligence can be enhanced by complementary functions of different agents. How to achieve time-varying formation tracking for heterogeneous swarm systems is crucial for cross-domain coordination, which has important theoretical value and practical significance. This important book presents a systematic theoretical approach and control framework on the time-varying formation tracking for high-order heterogeneous swarm systems. Distributed controller design and stability analysis of closed-loop systems for several specific formation tracking problems are provided. Furthermore, the proposed control approaches are applied to practical cooperative experiment platforms composed of UAVs and UGVs, and several formation tracking experiments are carried out to further verify the effectiveness of the theories.

Unmanned Aircraft Systems (UAS) have seen unprecedented levels of growth during the last decade in both military and civilian domains. However, it is anticipated that civilian applications will be dominant in the future, although there are still barriers to be overcome and technical challenges to be met. For example, integrating UAS into civilian space, fully autonomous navigation, see-detect-and-avoid systems, smart UAS designs, system integration, vision-based navigation, logistics and training, to name but a few areas, will be of prime importance in the near future. This special volume is the outcome of research presented at the International Symposium on Unmanned Aerial Vehicles, held in Dubai in June 2010, and presents state-of-the-art findings on topics related to: UAS operations and integration into the national airspace system; UAS navigation and control; micro-, mini-, small UAVs; UAS simulation testbeds and frameworks; UAS research platforms and applications; UAS applications. This book aims at serving as a guide tool on UAS for engineers and practitioners, academics, government agencies and industry. This is a hardbound spinoff from the Journal of Intelligent and Robotic Systems, Volume 61:1-4, 2011.

The essence of this work is the control of electromechanical systems, such as manipulators, electric machines, and power converters. The common thread that links together the results presented here is the passivity property, which is at present in numerous electrical and mechanical systems, and which has great relevance in control engineering at this time. Amongst other topics, the authors cover: Euler-Lagrange Systems, Mechanical Systems, Generalised AC Motors, Induction Motor Control, Robots with AC Drives, and Perspectives and Open Problems. The authors have extensive experience of research and application in the field of control of electromechanical systems, which they have summarised here in this self-contained volume. While written in a strictly mathematical way, it is also elementary, and will be accessible to a wide-ranging audience, including both practitioners and researchers in this field, as well as students.

The Chinese Society of Aeronautics and Astronautics holds the Youth Science and Technology Forum biannually, which aims to assess the state of aviation science and technology, recognize advanced scientific and technological accomplishments, foster the development of young aviation science and technology talents, and provide a platform for young science and technology workers to track the frontier of science and technology, exchange novel ideas, and accurately meet the needs of the aviation industry. This book contains original, peer-reviewed research papers from the conference. Topics covered include, but are not limited to, navigation, guidance and control technologies, key technologies for aircraft design and overall optimization, aviation test technologies, aviation airborne systems, electromechanical technologies, structural design, aerodynamics and flight mechanics, other related technologies, advanced aviation materials and manufacturing technologies, advanced aviation propulsion technologies, and civil aviation transportation. Researchers, engineers, and students find this book to be a useful resource because the articles provided here discuss the most recent advancements in aviation science and technology.

This book is the first comprehensive book about reservoir computing (RC). RC is a powerful and broadly applicable computational framework based on recurrent neural networks. Its advantages lie in small training data set requirements, fast training, inherent memory and high flexibility for various hardware implementations. It originated from computational neuroscience and machine learning but has, in recent years, spread dramatically, and has been introduced into a wide variety of fields, including complex systems science, physics, material science, biological science, quantum machine learning, optical communication systems, and robotics. Reviewing the current state of the art and providing a concise guide to the field, this book introduces readers to its basic concepts, theory, techniques, physical implementations and applications. The book is sub-structured into two major parts: theory and physical implementations. Both parts consist of a compilation of chapters, authored by leading experts in their respective fields. The first part is devoted to theoretical developments of RC, extending the framework from the conventional recurrent neural network context to a more general dynamical systems context. With this broadened perspective, RC is not restricted to the area of machine learning but is being connected to a much wider class of systems. The second part of the book focuses on the utilization of physical dynamical systems as reservoirs, a framework referred to as physical reservoir computing. A variety of physical systems and substrates have already been suggested and used for the implementation of reservoir computing. Among these physical systems which cover a wide range of spatial and temporal scales, are mechanical and optical systems, nanomaterials, spintronics, and quantum many body systems. This book offers a valuable resource for researchers (Ph.D. students and experts alike) and practitioners working in the field of machine learning, artificial intelligence, robotics, neuromorphic computing, complex systems, and physics.

This book tackles the latest research trends in technology acceptance models and theories. It presents high-quality empirical and review studies focusing on the main theoretical models and their applications across various technologies and contexts. It also provides insights into the theoretical and practical aspects of different technological innovations that assist decision-makers in formulating the required policies and procedures for adopting a specific technology.

This book includes high-quality research papers presented at Symposium on Power Electronic and Renewable Energy Systems Control (PERESC 2020), which is held at the School of Electrical Sciences, IIT Bhubaneswar, Odisha, India, during 4-5 December 2020. The book covers original work in power electronics which has greatly enabled integration of renewable and distributed energy systems, control of electric machine drives, high voltage system control and operation. The book is highly useful for academicians, engineers, researchers and students to be familiar with the latest state of the art in power electronics technology and its applications.

This book introduces modeling and simulation of linear time invariant systems and demonstrates how these translate to systems engineering, mechatronics engineering, and biomedical engineering. It is organized into nine chapters that follow the lectures used for a one-semester course on this topic, making it appropriate for students as well as researchers. The author discusses state space modeling derived from two modeling techniques and the analysis of the system and usage of modeling in control systems design. It also contains a unique chapter on multidisciplinary energy systems with a special focus on bioengineering systems and expands upon how the bond graph augments research in biomedical and bio-mechatronics systems.

As control systems become more complex and are expected to perform tasks in unknown and extreme environments, they may be subject to various types of faults in their sensors, actuators or other components. It is crucial to be able to diagnose the occurrence of faults and to repair them in order to maintain, guarantee, and improve the overall safety, reliability, and performance of the systems. This book addresses the design challenges of developing and implementing novel integrated fault diagnosis and control technologies for complex linear systems. Integrated Fault Diagnosis and Control Design of Linear Complex Systems considers linear time-invariant (LTI) systems under both time- and event-triggered frameworks. The book initially develops novel methodologies for the problem of integrated fault diagnosis and control of LTI systems to address current design challenges. The results obtained are then extended to a number of complex linear systems, specifically to Markovian jump systems as well as to cooperative multi-agent systems.

"Robust Output Feedback H-infinity Control and Filtering for Uncertain Linear Systems" discusses new and meaningful findings on robust output feedback H-infinity control and filtering for uncertain linear systems, presenting a number of useful and less conservative design results based on the linear matrix inequality (LMI) technique. Though primarily intended for graduate students in control and filtering, the book can also serve as a valuable reference work for researchers wishing to explore the area of robust H-infinity control and filtering of uncertain systems. Dr. Xiao-Heng Chang is a Professor at the College of Engineering, Bohai University, China.

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

This book presents best selected papers presented at the 4th International Conference on Smart Computing and Informatics (SCI 2020), held at the Department of Computer Science and Engineering, Vasavi College of Engineering (Autonomous), Hyderabad, Telangana, India. It presents advanced and multi-disciplinary research towards the design of smart computing and informatics. The theme is on a broader front which focuses on various innovation paradigms in system knowledge, intelligence and sustainability that may be applied to provide realistic solutions to varied problems in society, environment and industries. The scope is also extended towards the deployment of emerging computational and knowledge transfer approaches, optimizing solutions in various disciplines of science, technology and health care.

This book presents the human, cultural, and scientific contributions of professor Eliano Pessa, who recently passed away. His research interests and activities were varied, some of which included quantum physics, cognitive science and psychology, systems science, artificial intelligence, and alpinism. They were never disciplinary-separated issues, but rather some coherent dimensions of his interests in life. He lived and not only practiced interdisciplinarity and multiple dimensions; he considered it unacceptable to do only one thing in life. The contributors in this volume consider, discuss, interpret, and represent the multiplicity and interdisciplinarity experienced, lived and applied by Pessa. The chapters are inspired by, rebuild, and retrace such networked interests lived by him from the personal, cultural, and scientific points of view of the authors. This is true interdisciplinarity and usage of non-equivalences, honoring the richness of Pessa's contributions.

This book examines key issues in improving the efficiency of small and medium power boiler units by adding control systems for the fuel combustion process. The original models, algorithms, software and hardware of the system developed for controlling the fuel combustion process are presented. In turn, the book presents a methodology for assessing the influence of climatic factors on the combustion process, and proposes new methods for measuring the thermophysical characteristics, which require taking into account the concentration of oxygen in the air. The system developed here was implemented on a boiler of the NIISTU-5 type, which is widely used for heat power engineering in Ukraine and other Eastern European countries. Given its scope, the book offers a valuable asset for researchers and engineers, as well as lecturers and graduate students at higher education institutions dealing with heat engineering equipment.

This book discusses various applications of machine learning using a new approach, the dynamic wavelet fingerprint technique, to identify features for machine learning and pattern classification in time-domain signals. Whether for medical imaging or structural health monitoring, it develops analysis techniques and measurement technologies for the quantitative characterization of materials, tissues and structures by non-invasive means. Intelligent Feature Selection for Machine Learning using the Dynamic Wavelet Fingerprint begins by providing background information on machine learning and the wavelet fingerprint technique. It then progresses through six technical chapters, applying the methods discussed to particular real-world problems. Theses chapters are presented in such a way that they can be read on their own, depending on the reader's area of interest, or read together to provide a comprehensive overview of the topic. Given its scope, the book will be of interest to practitioners, engineers and researchers seeking to leverage the latest advances in machine learning in order to develop solutions to practical problems in structural health monitoring, medical imaging, autonomous vehicles, wireless technology, and historical conservation.

This monograph explores the analysis and design of model-free optimal control systems based on reinforcement learning (RL) theory, presenting new methods that overcome recent challenges faced by RL. New developments in the design of sensor data efficient RL algorithms are demonstrated that not only reduce the requirement of sensors by means of output feedback, but also ensure optimality and stability guarantees. A variety of practical challenges are considered, including disturbance rejection, control constraints, and communication delays. Ideas from game theory are incorporated to solve output feedback disturbance rejection problems, and the concepts of low gain feedback control are employed to develop RL controllers that achieve global stability under control constraints. Output Feedback Reinforcement Learning Control for Linear Systems will be a valuable reference for graduate students, control theorists working on optimal control systems, engineers, and applied mathematicians.

The proceedings of the 4th Stability and Control Processes Conference are focused on modern applied mathematics, stability theory, and control processes. The conference was held in recognition of the 90th birthday of Professor Vladimir Ivanovich Zubov (1930-2000). This selection of papers reflects the wide-ranging nature of V. I. Zubov's work, which included contributions to the development of the qualitative theory of differential equations, the theory of rigid body motion, optimal control theory, and the theory of electromagnetic fields. It helps to advance many aspects of the theory of control systems, including questions of motion stability, nonlinear oscillations in control systems, navigation and reliability of control devices, vibration theory, and quantization of orbits. The disparate applications covered by the book - in mechanical systems, game theory, solid-state physics, socio-economic systems and medical and biological systems, control automata and navigation - are developments from Professor Zubov's in-depth studies on the theory of stability of motion, the theory of automatic control and the theory of the motions of optimal processes. Stability and Control Processes presents research continuing the legacy of V. I. Zubov and updates it with sections focused on intelligence-based control. These proceedings will be of interest to academics, professionals working in industry and researchers alike.

The proceedings present selected research papers from the CIAC2021, held in Zhanjiang, China on Nov 5-7, 2021. It covers a wide range of topics including intelligent control, robotics, artificial intelligence, pattern recognition, unmanned systems, IoT and machine learning. It includes original research and the latest advances in the field of intelligent automation. Engineers and researchers from academia, industry, and government can gain valuable insights into solutions combining ideas from multiple disciplines in this field.

This book intends to introduce some recent results on passivity of complex dynamical networks with single weight and multiple weights. The book collects novel research ideas and some definitions in complex dynamical networks, such as passivity, output strict passivity, input strict passivity, finite-time passivity, and multiple weights. Furthermore, the research results previously published in many flagship journals are methodically edited and presented in a unified form. The book is likely to be of interest to university researchers and graduate students in Engineering and Mathematics who wish to study the passivity of complex dynamical networks.

This book reports the new results of intelligent robot with hand-eye-brain, from the interdisciplinary perspective of information science and neuroscience. It collects novel research ideas on attractive region in environment (ARIE), intrinsic variable preserving manifold learning (IVPML) and biologically inspired visual congnition, which are theoretically important but challenging to develop the intelligent robot. Furthermore, the book offers new thoughts on the possible future development of human-inspired robotics, with vivid illustrations. The book is useful for researchers, R&D engineers and graduate students working on intelligent robots.

This book presents operational and practical issuesof automotive mechatronics with special emphasis on the heterogeneous automotive vehicle systems approach, and is intended as a graduate text as well as a reference for scientists and engineers involved in the design of automotive mechatronic control systems.

As the complexity of automotive vehicles increases, so does the dearth of high competence, multi-disciplined automotive scientists and engineers. This book provides a discussion into the type of mechatronic control systems found in modernvehicles and the skills required by automotive scientists and engineers working in this environment.

Divided into two volumes and five parts, "Automotive Mechatronics" aimsat improving automotive mechatronics education and emphasises the trainingof students experimental hands-on abilities, stimulating and promoting experience among high education institutes and produce more automotive mechatronics and automation engineers.

The main subject that are treated are:

VOLUME I: RBW or XBW unibody or chassis-motion mechatronic control hypersystems;DBW AWD propulsion mechatronic control systems; BBW AWB dispulsion mechatronic control systems;

VOLUME II: SBW AWS diversion mechatronic control systems; ABW AWA suspension mechatronic control systems.

This volumewas developed for undergraduate and postgraduate students as wellas for professionals involved in all disciplines related to the design or research and development of automotive vehicle dynamics, powertrains, brakes, steering, and shock absorbers (dampers). Basic knowledge of college mathematics, college physics, and knowledge of the functionality of automotive vehicle basic propulsion, dispulsion, conversion and suspension systems is required. "

This book belongs to the subject of control and systems theory. The discrete-time adaptive iterative learning control (DAILC) is discussed as a cutting-edge of ILC and can address random initial states, iteration-varying targets, and other non-repetitive uncertainties in practical applications. This book begins with the design and analysis of model-based DAILC methods by referencing the tools used in the discrete-time adaptive control theory. To overcome the extreme difficulties in modeling a complex system, the data-driven DAILC methods are further discussed by building a linear parametric data mapping between two consecutive iterations. Other significant improvements and extensions of the model-based/data-driven DAILC are also studied to facilitate broader applications. The readers can learn the recent progress on DAILC with consideration of various applications. This book is intended for academic scholars, engineers and graduate students who are interested in learning control, adaptive control, nonlinear systems, and related fields.

The book provides a systematic and in-depth introduction to distributed event-triggered cooperative control for multi-agent systems from a theoretical perspective, which will be of particular interest to the readers. The included major research topics include: a unified design and analysis framework for centralized, clustered and distributed event-triggered schemes; fully distributed design for event/self-triggered schemes; resilient event-triggered control under malicious attacks; and various methods to aovid Zeno behavior. The comprehensive and systematic treatment of event-triggered communication and control in multi-agent system is one of the major features of the book, which is particularly suited for readers who are interested in learning principles and methods to deal with communication constraints in multi-agent systems and to design energy-saving control protocols. The book can benefit researchers, engineers, and graduate students in the fields of complex networks, smart grids, applied mathematics, electrical and electronic engineering, and computer engineering, etc.

This book presents selected papers from the 1st International Conference on Industry 4.0 and Advanced Manufacturing held at the Indian Institute of Science, Bangalore and includes deliberations from stakeholders in manufacturing and Industry 4.0 on the nature, needs, challenges, opportunities, problems, and solutions in these transformational areas. Special emphasis is placed on exploring avenues for creating a vision of, and enablers for, sustainable, affordable, and human-centric Industry 4.0. The book showcases cutting edge practice, research, and educational innovation in this crucial and rapidly evolving area. This book will be useful to researchers in academia and industry, and will also be useful to policymakers involved in creating ecosystems for implementation of Industry 4.0.

This book introduces a passivity-based approach which simplifies the controller design task for AC-motors. It presents the application of this novel approach to several classes of AC motors, magnetic levitation systems, microelectromechanical systems (MEMS) and rigid robot manipulators actuated by AC motors. The novel passivity-based approach exploits the fact that the natural energy exchange existing between the mechanical and the electrical subsystems allows the natural cancellation of several high order terms during the stability analysis. This allows the authors to present some of the simplest controllers proposed in scientific literature, but provided with formal stability proofs. These simple control laws will be of use to practitioners as they are robust with respect to numerical errors and noise amplification, and are provided with tuning guidelines. Energy-based Control of Electromechanical Systems is intended for both theorists and practitioners. Therefore, the stability proofs are not based on abstract mathematical ideas but Lyapunov stability theory. Several interpretations of the proofs are given along the body of the book using simple energy ideas and the complete proofs are included in appendices. The complete modeling of each motor studied is also presented, allowing for a thorough understanding. 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.