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 book examines the burgeoning revolution in the construction industry known as Construction 4.0, the attendant need for re-skilling human resources, and key stakeholders' roles in developing the required skills for Construction 4.0. It views the lack of 21st-century skills and skills gap in the industry as significant challenges limiting the uptake and implementation of Construction 4.0 technologies, especially in developing countries. In order to determine the skills required, this book examines the critical technologies of Construction 4.0, such as building information modelling (BIM), robotic construction, 3D printing and drones, which have transformed the construction industry, thereby creating digital, intelligent and sustainable construction solutions. Furthermore, the book considers the benefits, risks and relevant skills required to implement Construction 4.0 technologies.

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.

This book presents some post-estimation and predictions strategies for the host of useful statistical models with applications in data science. It combines statistical learning and machine learning techniques in a unique and optimal way. It is well-known that machine learning methods are subject to many issues relating to bias, and consequently the mean squared error and prediction error may explode. For this reason, we suggest shrinkage strategies to control the bias by combining a submodel selected by a penalized method with a model with many features. Further, the suggested shrinkage methodology can be successfully implemented for high dimensional data analysis. Many researchers in statistics and medical sciences work with big data. They need to analyse this data through statistical modelling. Estimating the model parameters accurately is an important part of the data analysis. This book may be a repository for developing improve estimation strategies for statisticians. This book will help researchers and practitioners for their teaching and advanced research, and is an excellent textbook for advanced undergraduate and graduate courses involving shrinkage, statistical, and machine learning. The book succinctly reveals the bias inherited in machine learning method and successfully provides tools, tricks and tips to deal with the bias issue. Expertly sheds light on the fundamental reasoning for model selection and post estimation using shrinkage and related strategies. This presentation is fundamental, because shrinkage and other methods appropriate for model selection and estimation problems and there is a growing interest in this area to fill the gap between competitive strategies. Application of these strategies to real life data set from many walks of life. Analytical results are fully corroborated by numerical work and numerous worked examples are included in each chapter with numerous graphs for data visualization. The presentation and style of the book clearly makes it accessible to a broad audience. It offers rich, concise expositions of each strategy and clearly describes how to use each estimation strategy for the problem at hand. This book emphasizes that statistics/statisticians can play a dominant role in solving Big Data problems, and will put them on the precipice of scientific discovery. The book contributes novel methodologies for HDDA and will open a door for continued research in this hot area. The practical impact of the proposed work stems from wide applications. The developed computational packages will aid in analyzing a broad range of applications in many walks of life.

The book presents an overview of current research on biologically inspired autonomous robotics from the perspective of some of the most relevant researchers in this area. The book crosses several boundaries in the field of robotics and the closely related field of artificial life. The key aim throughout the book is to obtain autonomy at different levels. From the basic motor behavior in some exotic robot architectures right through to the planning of complex behaviors or the evolution of robot control structures, the book explores different degrees and definitions of autonomous behavior. These behaviors are supported by a wide variety of modeling techniques: structural grammars, neural networks, and fuzzy logic and evolution underlies many of the development processes. Thus this text can be used by scientists and students interested in these areas and provides a general view of the field for a more general audience.

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.

Technology has created innovative new prospects for manufacturing industries with Industry 4.0 and has helped further the growth of the manufacturing sector. This book focuses on the next stage, which is Industry 5.0, and the steps in taking automation to that next level by increasing processes and operational efficiency, as well as reducing workforce size. Industry 5.0: The Future of the Industrial Economy discusses the integration of product, process, machine, software, and industrial robots in realizing Industry 5.0. It covers the dual integration of human intelligence with machine intelligence and reviews the results of making use of Industrial Internet of Things (IIoT) and Artificial Intelligence (AI). The creation of a new category of robots named Collaborative Robots (Cobots) specifically designed to speed up the manufacturing process and profitability is explored. This book also explores how to reduce waste in product design through the manufacturing process and offers more personalized and customized products for customers. Manufacturing, design, industrial, and mechanical engineers, as well as practicing professionals, will find this book of interest. Management executives, CIOs, CEOs, IT professionals, and academics will also find something of value in this book that takes Industry 4.0 to Industry 5.0 and beyond.

This book is a collection of high-quality research articles. The book includes topics specific to the emerging areas of control for robotic systems, wireless communication, and development of embedded systems for robotic applications. The book integrates three important aspects of automation, namely (i) communication, (ii) control, and (iii) embedded design for robotic applications. This book is unique as it provides a unified framework for analysis, design, and deployment of the robotic applications across various engineering and non-engineering disciplines including the three primary aspects mentioned above. Furthermore, the emerging research and development work pertaining to the deployment of intelligent, nonlinear, and embedded control for robotic system for non-standard operating environment due to the widespread application of robotics technology for societal benefit is also a focal point of the book.

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 theoretical modeling and numerical simulations applied to drive several applications towards Industrial Revolution 4.0 (IR 4.0). The topics discussed range from theoretical parts to extensive simulations involving many efficient algorithms as well as various statistical techniques. This book is suitable for postgraduate students, researchers as well as other scientists who are working in mathematics, statistics and numerical modeling and simulation.

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.

Human Inspired Dexterity in Robotic Manipulation provides up-to-date research and information on how to imitate humans and realize robotic manipulation. Approaches from both software and hardware viewpoints are shown, with sections discussing, and highlighting, case studies that demonstrate how human manipulation techniques or skills can be transferred to robotic manipulation. From the hardware viewpoint, the book discusses important human hand structures that are key for robotic hand design and how they should be embedded for dexterous manipulation. This book is ideal for the research communities in robotics, mechatronics and automation.

This book offers readers essential insights into system design for deep space probes and describes key aspects such as system design, orbit design, telecommunication, GNC, thermal control, propulsion, aerobraking and scientific payload. Each chapter includes the basic principles, requirements analysis, procedures, equations and diagrams, as well as practical examples that will help readers to understand the research on each technology and the major concerns when it comes to developing deep space probes. An excellent reference resource for researchers and engineers interested in deep space exploration, it can also serve as a textbook for university students and those at institutes involved in aerospace.

This book consolidates the current state of knowledge on implementing cooperating robot-based systems to increase the flexibility of manufacturing systems. It is based on the concrete experiences of experts, practitioners, and engineers in implementing cooperating robot systems for more flexible manufacturing systems. Thanks to the great variety of manufacturing systems that we had the opportunity to study, a remarkable collection of methods and tools has emerged. The aim of the book is to share this experience with academia and industry practitioners seeking to improve manufacturing practice. While there are various books on teaching principles for robotics, this book offers a unique opportunity to dive into the practical aspects of implementing complex real-world robotic applications. As it is used in this book, the term "cooperating robots" refers to robots that either cooperate with one another or with people. The book investigates various aspects of cooperation in the context of implementing flexible manufacturing systems. Accordingly, manufacturing systems are the main focus in the discussion on implementing such robotic systems. The book begins with a brief introduction to the concept of manufacturing systems, followed by a discussion of flexibility. Aspects of designing such systems, e.g. material flow, logistics, processing times, shop floor footprint, and design of flexible handling systems, are subsequently covered. In closing, the book addresses key issues in operating such systems, which concern e.g. decision-making, autonomy, cooperation, communication, task scheduling, motion generation, and distribution of control between different devices. Reviewing the state of the art and presenting the latest innovations, the book offers a valuable asset for a broad readership.

This book gathers the latest advances, innovations, and applications in the field of machine science and mechanical engineering, as presented by international researchers and engineers at the 11th International Conference on Machine and Industrial Design in Mechanical Engineering (KOD), held in Novi Sad, Serbia on June 10-12, 2021. It covers topics such as mechanical and graphical engineering, industrial design and shaping, product development and management, complexity, and system design. The contributions, which were selected by means of a rigorous international peer-review process, highlight numerous exciting ideas that will spur novel research directions and foster multidisciplinary collaborations.

The book is a compilation of selected papers from 2020 International Conference on Electrical and Electronics Engineering (ICEEE 2020) held in National Power Training Institute HQ (Govt. of India) on February 21 - 22, 2020. The work focuses on the current development in the fields of electrical and electronics engineering like power generation, transmission and distribution, renewable energy sources and technology, power electronics and applications, robotics, artificial intelligence and IoT, control, and automation and instrumentation, electronics devices, circuits and systems, wireless and optical communication, RF and microwaves, VLSI, and signal processing. The book is beneficial for readers from both academia and industry.

This book covers some selected problems of the descriptor integer and fractional order positive continuous-time and discrete-time systems. The book consists of 3 chapters, 4 appendices and the list of references. Chapter 1 is devoted to descriptor integer order continuous-time and discrete-time linear systems. In Chapter 2, descriptor fractional order continuous-time and discrete-time linear systems are considered. Chapter 3 is devoted to the stability of descriptor continuous-time and discrete-time systems of integer and fractional orders. In Appendix A, extensions of the Cayley-Hamilton theorem for descriptor linear systems are given. Some methods for computation of the Drazin inverse are presented in Appendix B. In Appendix C, some basic definitions and theorems on Laplace transforms and Z-transforms are given. Some properties of the nilpotent matrices are given in Appendix D.

This book describes the application of vision-sensing technologies in welding processes, one of the key technologies in intelligent welding manufacturing. Gas tungsten arc welding (GTAW) is one of the main welding techniques and has a wide range of applications in the manufacturing industry. As such, the book also explores the application of AI technologies, such as vision sensing and machine learning, in GTAW process sensing and feature extraction and monitoring, and presents the state-of-the-art in computer vision, image processing and machine learning to detect welding defects using non-destructive methods in order to improve welding productivity. Featuring the latest research from ORNL (Oak Ridge National Laboratory) using digital image correlation technology, this book will appeal to researchers, scientists and engineers in the field of advanced manufacturing.

This book gathers selected research papers presented at the Second International Conference on Energy Systems, Drives and Automations (ESDA 2019), held in Kolkata on 28-29 December 2019. It covers a broad range of topics in the fields of renewable energy, power management, drive systems for electrical machines and automation. Also discussing a variety of related tools and techniques, the book offers a valuable resource for researchers, professionals and students in electrical and mechanical engineering disciplines.