Thiseditedbookispublishedin honorofDr. GeorgeJ. Vachtsevanos, ourDr. V, c- rently Professor Emeritus, School of Electrical and Computer Engineering, Georgia Institute of Technology, on the occasion of his 70th birthday and for his more than 30 years of contribution to the discipline of Intelligent Control and its application to a wide spectrum of engineering and bioengineering systems. The book is nothing but a very small token of appreciation from Dr. V's former graduate students, his peers and colleagues in the profession - and not only - to the Scientist, the Engineer, the Professor, the mentor, but most important of all, to the friend and human being. All those who have met Dr. V over the years and haveinteractedwith himin someprofessionaland/orsocial capacityunderstandthis statement: Georgenevermadeanybodyfeelinferiortohim, hehelpedandsupported everybody, and he was there when anybody needed him I was not Dr. V's student. I rst met him and his wife Athena more than 26 years ago during one of their visits to RPI, in the house of my late advisor, Dr. George N. Saridis. Since then, I have been very fortunate to have had and continue to have interactions with him. It is not an exaggeration if I say that we all learned a lot from him.

The world of artificial systems is reaching hitherto undreamed-of levels of complexity. Surface traffic, electricity distribution, mobile communications, etc., demonstrate that problems are arising that are beyond classical scientific or engineering knowledge. In order that our ability to control such systems should not be hindered by lack of comprehension, there is an on-going effort to understand them.This book is an example of the types of approach that European researchers are using to tackle problems derived from systems' complexity. It has grown out of activities in the Control of Complex Systems (COSY) research program the goals of which are to promote multi-disciplinary activity leading to a deeper understanding and further development of control technologies for complex systems and if possible, to develop the theory underlying such systems. The material in this book represents a selection of the results of the COSY program and is organised as a collection of essays of varying nature: surveys of essential areas, discussion of specific problems, case studies, and benchmark problems.Topics covered include:Modelling complex physical systems;Passivity-based control of non-linear systems;Aspects of fault identification and fault tolerance;Control design;Learning control;Satellite attitude control.Complex systems appear in many different fields and for this reason this book should be of interest to scientists, researchers and industrial engineers with a broad spectrum of experience.

The controller area network (CAN) microcontroller communication protocol is now ubiquitous in a staggeringly wide range of transportation and industrial control applications.

This fully revised and updated new edition addresses the various challenges and open questions relating to CAN communication networks. Opening with a short introduction into the fundamentals of CAN, the book then examines the problems and solutions for the physical layout of networks, including EMC issues and topology layout. Additionally, a discussion of quality issues with a particular focus on test techniques is presented. Each chapter features a collection of illuminating insights and detailed technical information supplied by a selection of internationally-regarded experts from industry and academia.

Topics and features: presents thorough coverage of architectures, implementations and application of CAN transceiver, data link layer and so-called higher layer software; explains CAN EMC characteristics and countermeasures, as well as how to design CAN networks; demonstrates how to practically apply and test CAN systems; includes examples of real networks from diverse applications in automotive engineering, avionics, and home heating technology; includes a glossary of abbreviations, and a useful bibliography.

This comprehensive text will be an invaluable guide/reference for electronic engineers working with industrial control systems.

Computational kinematics is an enthralling area of science with a rich spectrum of problems at the junction of mechanics, robotics, computer science, mathematics, and computer graphics. The covered topics include design and optimization of cable-driven robots, analysis of parallel manipulators, motion planning, numerical methods for mechanism calibration and optimization, geometric approaches to mechanism analysis and design, synthesis of mechanisms, kinematical issues in biomechanics, construction of novel mechanical devices, as well as detection and treatment of singularities.

The results should be of interest for practicing and research engineers as well as Ph.D. students from the fields of mechanical and electrical engineering, computer science, and computer graphics.

- The book discusses the recent techniques in NGS data analysis which is the most needed material by biologists (students and researchers) in the wake of numerous genomic projects and the trend toward genomic research. - The book includes both theory and practice for the NGS data analysis. So, readers will understand the concept and learn how to do the analysis using the most recent programs. - The steps of application workflows are written in a manner that can be followed for related projects. - Each chapter includes worked examples with real data available on the NCBI databases. Programming codes and outputs are accompanied with explanation. - The book content is suitable as teaching material for biology and bioinformatics students. Meets the requirements of a complete semester course on Sequencing Data Analysis Covers the latest applications for Next Generation Sequencing Covers data reprocessing, genome assembly, variant discovery, gene profiling, epigenetics, and metagenomics

Most applications generate large datasets, like social networking and social influence programs, smart cities applications, smart house environments, Cloud applications, public web sites, scientific experiments and simulations, data warehouse, monitoring platforms, and e-government services. Data grows rapidly, since applications produce continuously increasing volumes of both unstructured and structured data. Large-scale interconnected systems aim to aggregate and efficiently exploit the power of widely distributed resources. In this context, major solutions for scalability, mobility, reliability, fault tolerance and security are required to achieve high performance and to create a smart environment. The impact on data processing, transfer and storage is the need to re-evaluate the approaches and solutions to better answer the user needs. A variety of solutions for specific applications and platforms exist so a thorough and systematic analysis of existing solutions for data science, data analytics, methods and algorithms used in Big Data processing and storage environments is significant in designing and implementing a smart environment. Fundamental issues pertaining to smart environments (smart cities, ambient assisted leaving, smart houses, green houses, cyber physical systems, etc.) are reviewed. Most of the current efforts still do not adequately address the heterogeneity of different distributed systems, the interoperability between them, and the systems resilience. This book will primarily encompass practical approaches that promote research in all aspects of data processing, data analytics, data processing in different type of systems: Cluster Computing, Grid Computing, Peer-to-Peer, Cloud/Edge/Fog Computing, all involving elements of heterogeneity, having a large variety of tools and software to manage them. The main role of resource management techniques in this domain is to create the suitable frameworks for development of applications and deployment in smart environments, with respect to high performance. The book focuses on topics covering algorithms, architectures, management models, high performance computing techniques and large-scale distributed systems.

Research and development of various parallel mechanism applications in engineering are now being performed more and more actively in every industrial field. Parallel robot based machine tools development is considered a key technology of robot applications in manufacturing industries. The material covered here describes the basic theory, approaches, and algorithms in the field of parallel robot based machine tools. In addition families of new alternative mechanical architectures which can be used for machine tools with parallel architecture are introduced. Given equal importance is the design of mechanism systems such as kinematic analysis, stiffness analysis, kinetostatic modeling, and optimization.

The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the modeling process. This book describes techniques for finding the best representations of predictors for modeling and for nding the best subset of predictors for improving model performance. A variety of example data sets are used to illustrate the techniques along with R programs for reproducing the results.

Brain and Behavior Computing offers insights into the functions of the human brain. This book provides an emphasis on brain and behavior computing with different modalities available such as signal processing, image processing, data sciences, statistics further it includes fundamental, mathematical model, algorithms, case studies, and future research scopes. It further illustrates brain signal sources and how the brain signal can process, manipulate, and transform in different domains allowing researchers and professionals to extract information about the physiological condition of the brain. Emphasizes real challenges in brain signal processing for a variety of applications for analysis, classification, and clustering. Discusses data sciences and its applications in brain computing visualization. Covers all the most recent tools for analysing the brain and it's working. Describes brain modeling and all possible machine learning methods and their uses. Augments the use of data mining and machine learning to brain computer interface (BCI) devices. Includes case studies and actual simulation examples. This book is aimed at researchers, professionals, and graduate students in image processing and computer vision, biomedical engineering, signal processing, and brain and behavior computing.

The volume contains peer-reviewed proceedings of EPREC 2021 with a focus on control applications in the modern power system. The book includes original research and case studies that present recent developments in the control system, especially load frequency control, wide-area monitoring, control & instrumentation, optimization, intelligent control, energy management system, SCADA systems, etc. The book will be a valuable reference guide for beginners, researchers, and professionals interested in advancements in the control system.

This book focuses on the nonlinear dynamics based on the vector fields with univariate quadratic functions. This book is a unique monograph for two-dimensional quadratic nonlinear systems. It provides different points of view about nonlinear dynamics and bifurcations of the quadratic dynamical systems. Such a two-dimensional dynamical system is one of simplest dynamical systems in nonlinear dynamics, but the local and global structures of equilibriums and flows in such two-dimensional quadratic systems help us understand other nonlinear dynamical systems, which is also a crucial step toward solving the Hilbert's sixteenth problem. Possible singular dynamics of the two-dimensional quadratic systems are discussed in detail. The dynamics of equilibriums and one-dimensional flows in two-dimensional systems are presented. Saddle-sink and saddle-source bifurcations are discussed, and saddle-center bifurcations are presented. The infinite-equilibrium states are switching bifurcations for nonlinear systems. From the first integral manifolds, the saddle-center networks are developed, and the networks of saddles, source, and sink are also presented. This book serves as a reference book on dynamical systems and control for researchers, students, and engineering in mathematics, mechanical, and electrical engineering.

This book focuses on the stabilization and model predictive control of interconnected systems with mixed connection configurations. It introduces the concept of dissipation-based quadratic constraint for developing attractivity assurance methods for interconnected systems. In order to develop these methods, distributed and decentralized architectures are employed, whereby the communication between subsystems is fully connected, partially connected, or completely disconnected. Given that the control inputs are entirely or partially decoupled between subsystems and no additional constraints are imposed on the interactive variables beyond the coupling constraint itself, the proposed approaches can be used with various types of systems and applications. Further, the book describes how the effects of coupling delays and data losses in device networks are resolved. From a practical perspective, the innovations presented are of benefit in applications in a broad range of fields, including the process and manufacturing industries, networked robotics, and network-centric systems such as chemical process systems, power systems, telecommunication networks, transportation networks, and, no less importantly, supply chain automation.

This book helps readers evaluate and specificy the best Warehouse Management System (WMS) for their need. The advice is based on practical knowledge, describing in detail fundamental processes and technologies needed for a basic understanding. New approaches in the structure and design of WMS are presented, along with discussion of the limitations of current systems. The book shows how to operate a simple WMS based on the open-source initiative myWMS.

Given their key position in the process control industry, process monitoring techniques have been extensively investigated by industrial practitioners and academic control researchers. Multivariate statistical process control (MSPC) is one of the most popular data-based methods for process monitoring and is widely used in various industrial areas. Effective routines for process monitoring can help operators run industrial processes efficiently at the same time as maintaining high product quality.

"Multivariate Statistical Process Control"" "reviews the developments and improvements that have been made to MSPC over the last decade, and goes on to propose a series of new MSPC-based approaches for complex process monitoring. These new methods are demonstrated in several case studies from the chemical, biological, and semiconductor industrial areas.

Control and process engineers, and academic researchers in the process monitoring, process control and fault detection and isolation (FDI) disciplines will be interested in this book. It can also be used to provide supplementary material and industrial insight for graduate and advanced undergraduate students, and graduate engineers.

Advances in Industrial Control aims to report and encourage 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."

Artificial Intelligence for Capital Market throws light on application of AI/ML techniques in the financial capital markets. This book discusses the challenges posed by the AI/ML techniques as these are prone to "black box" syndrome. The complexity of understanding the underlying dynamics for results generated by these methods is one of the major concerns which is highlighted in this book: Features: Showcases artificial intelligence in finance service industry Explains Credit and Risk Analysis Elaborates on cryptocurrencies and blockchain technology Focuses on optimal choice of asset pricing model Introduces Testing of market efficiency and Forecasting in Indian Stock Market This book serves as a reference book for Academicians, Industry Professional, Traders, Finance Mangers and Stock Brokers. It may also be used as textbook for graduate level courses in financial services and financial Analytics.

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

Fault Diagnosis and Fault-Tolerant Control and Guidance for Aerospace demonstrates the attractive potential of recent developments in control for resolving such issues as flight performance, self protection and extended-life structures. Importantly, the text deals with a number of practically significant considerations: tuning, complexity of design, real-time capability, evaluation of worst-case performance, robustness in harsh environments, and extensibility when development or adaptation is required. Coverage of such issues helps to draw the advanced concepts arising from academic research back towards the technological concerns of industry. Initial coverage of basic definitions and ideas and a literature review gives way to a treatment of electrical flight control system failures: oscillatory failure, runaway, and jamming. Advanced fault detection and diagnosis for linear and linear-parameter-varying systems are described. Lastly recovery strategies appropriate to remaining actuator/sensor/communications resources are developed. The authors exploit experience gained in research collaboration with academic and major industrial partners to validate advanced fault diagnosis and fault-tolerant control techniques with realistic benchmarks or real-world aeronautical and space systems. Consequently, the results presented in Fault Diagnosis and Fault-Tolerant Control and Guidance for Aerospace, will be of interest in both academic and aerospatial-industrial milieux.

This book gathers contributions on analytical, numerical, and application aspects of time-delay systems, under the paradigm of control theory, and discusses recent advances in these different contexts, also highlighting the interdisciplinary connections. The book will serve as a useful tool for graduate students and researchers in the fields of dynamical systems, automatic control, numerical methods, and functional analysis.

This book is concerned with Intelligent Control methods and applications. The field of intelligent control has been expanded very much during the recent years and a solid body of theoretical and practical results are now available. These results have been obtained through the synergetic fusion of concepts and techniques from a variety of fields such as automatic control, systems science, computer science, neurophysiology and operational research. Intelligent control systems have to perform anthropomorphic tasks fully autonomously or interactively with the human under known or unknown and uncertain environmental conditions. Therefore the basic components of any intelligent control system include cognition, perception, learning, sensing, planning, numeric and symbolic processing, fault detection/repair, reaction, and control action. These components must be linked in a systematic, synergetic and efficient way. Predecessors of intelligent control are adaptive control, self-organizing control, and learning control which are well documented in the literature. Typical application examples of intelligent controls are intelligent robotic systems, intelligent manufacturing systems, intelligent medical systems, and intelligent space teleoperators. Intelligent controllers must employ both quantitative and qualitative information and must be able to cope with severe temporal and spatial variations, in addition to the fundamental task of achieving the desired transient and steady-state performance. Of course the level of intelligence required in each particular application is a matter of discussion between the designers and users. The current literature on intelligent control is increasing, but the information is still available in a sparse and disorganized way.

The time evol11tion of many physical phenomena in nat11re can be de scribed by partial differential eq11ations. To analyze and control the dynamic behavior of s11ch systems. infinite dimensional system theory was developed and has been refined over the past several decades. In recent years. stim11lated by the applications arising from space exploration. a11tomated manufact11ring, and other areas of technological advancement, major progress has been made in both theory and control technology associated with infinite dimensional systems. For example, new conditions in the time domain and frequency domain have been derived which guarantee that a Co-semigroup is exponen tially stable; new feedback control laws helVe been proposed to exponentially;;tabilize beam. wave, and thermoelastic equations; and new methods have been developed which allow us to show that the spectrum-determined growth condition holds for a wide class of systems. Therefore, there is a need for a reference book which presents these restllts in an integrated fashion. Complementing the existing books, e. g . . 1]. 41]. and 128]. this book reports some recent achievements in stability and feedback stabilization of infinite dimensional systems. In particular, emphasis will be placed on the second order partial differential equations. such as Euler-Bernoulli beam equations. which arise from control of numerous mechanical systems stich as flexible robot arms and large space structures. We will be focusing on new results. most of which are our own recently obtained research results."

This book provides an in-depth overview of artificial intelligence and deep learning approaches with case studies to solve problems associated with biometric security such as authentication, indexing, template protection, spoofing attack detection, ROI detection, gender classification etc. This text highlights a showcase of cutting-edge research on the use of convolution neural networks, autoencoders, recurrent convolutional neural networks in face, hand, iris, gait, fingerprint, vein, and medical biometric traits. It also provides a step-by-step guide to understanding deep learning concepts for biometrics authentication approaches and presents an analysis of biometric images under various environmental conditions. This book is sure to catch the attention of scholars, researchers, practitioners, and technology aspirants who are willing to research in the field of AI and biometric security.

This monograph is focused on control law design methods for asymptotic tracking and disturbance rejection in the presence of uncertainties. The methods are based on adaptive implementation of the Internal Model Principle (IMP). The monograph shows how this principle can be applied to the problems of asymptotic rejection/tracking of a priori uncertain exogenous signals for linear and nonlinear plants with known and unknown parameters. The book begins by introducing the problems of adaptive control, the challenges that are faced, modern methods and an overview of the IMP. It then introduces special observers for uncertain exogeneous signals affecting linear and nonlinear systems with known and unknown parameters. The basic algorithms of adaptation applied to the canonical closed-loop error models are presented. The authors then address the systematic design of adaptive systems for asymptotic rejection/tracking of a priori uncertain exosignals. The monograph also discusses the adaptive rejection/tracking of a priori uncertain exogenous signals in systems with input delay, the problems of performance improvement in disturbance rejection and reference tracking and the issue of robustness of closed-loop systems. Adaptive Regulation provides a systematic discussion of the IMP applied to a variety of control problems, making it of interest to researchers and industrial practitioners.

This book addresses the problem of multi-agent systems, considering that it can be interpreted as a generalized multi-synchronization problem. From manufacturing tasks, through encryption and communication algorithms, to high-precision experiments, the simultaneous cooperation between multiple systems or agents is essential to successfully carrying out different modern activities, both in academy and industry. For example, the coordination of multiple assembler robots in manufacturing lines. These agents need to synchronize. The first two chapters of the book describe the synchronization of dynamical systems, paying special attention to the synchronization of non-identical systems. Following, the third chapter presents an interesting application of the synchronization phenomenon for state estimation. Subsequently, the authors fully address the multi-agent problem interpreted as multi-synchronization. The final chapters introduce the reader to a more complex problem, the synchronization of systems governed by partial differential equations, both of integer and fractional order. The book aimed at graduates, postgraduate students and researchers closely related to the area of automatic control. Previous knowledge of linear algebra, classical and fractional calculus is requested, as well as some fundamental notions of graph theory.

This book reviews the advances in data gathering and processing in the biotech laboratory environment, and it sheds new lights on the various aspects that are necessary for the implementation of intelligent laboratory architecture and infrastructure. Smart technologies are increasingly dominating our everyday lives and have become an indispensable part of the industrial environment. The laboratory environment, which has long been rather conservative, has also set out to adapt smart technologies with regards to Industry 4.0 and the Internet of Things (IoT) for the laboratory. Due to the heterogeneity of the existing infrastructure and the often complex work processes, standardization is slow, e.g. to implement device interfaces or standardized driver protocols, which are urgently needed to generate standardized data streams that would be immanent for post-processing of data. Divided into 9 chapters, this book offers an authoritative overview of the diverse aspects in the generation and recording of uniform data sets in the laboratory, and in the processing of the data and enabling seamless processing towards machine learning and artificial intelligence. In the first part of the book, readers will find more about high throughout systems, automation, robotics, and the evolution of technology in the laboratory. The second part of the book is devoted to standardization in lab automation, in which readers will learn more about some regulatory aspects, the SiLA2 standards, the OPC LADS (Laboratory and Analytical Device Standard), and FAIR Data infrastructure